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Abstract The mathematical model of heating substation, which is an important part of district heating system, is presented in this paper. The main components of district heating substation system, from the automatic control perspective, that are observed in this paper are heat exchanger and three-way valve. Presented mathematical model is developed so it could operate in real-time, since the crucial aspect of development, deployment and testing of new control techniques and optimization algorithms is their accurate validation on the real system. However, the accessibility to a real system is often not possible. Corresponding to this, an alternative is the existence of the correct mathematical model of a process, with the ability to operate in real-time. First, the presented mathematical model of district heating substation is decomposed to the simpler models of its main elements, in order to provide the analysis of the various parameters on the model performance through numerical simulation. Second, a real-time model is developed in LabVIEW software package and deployed on the embedded controller with a real-time processor as a three-layer application which enables data acquisition and communication with a programmable controller. [ABSTRACT FROM AUTHOR]

Abstract Corruption is one of the barriers to achieving sustainable development goals (SDGs), which is associated with the lack of integrity. The objective of the paper is to examine the extent of integrity framework information disclosure on Malaysian and Indonesian local authorities' websites using the coercive isomorphism tenet. The data collected in this study were based on a content analysis of inclusion or exclusion of integrity framework information disclosed on 51 Malaysian and 34 Indonesian local authorities' websites. This paper is significant for the following reasons. Based on the website disclosures, the 34 Indonesian local authorities or provinces outperformed Malaysia's 51 city and municipal councils' disclosures. The average website disclosure for Indonesia was 29 items out of 47 items under study as compared to just four items disclosed in Malaysia. Indonesian local authorities are more proactive in the integrity initiative implementation, which is translated into reporting as influenced by the external coercive forces: legitimacy, public visibility, public sector reform and institutional support structures. The findings would assist in helping regulatory authorities and policy makers to strengthen their mechanisms in upholding integrity. This paper considers the institutional theory of isomorphism mechanism, namely, coercive that enhances the understanding of integrity framework disclosure and adds to the pool of literature. Graphical abstract Image 10581 Highlights • The Indonesian local authorities disclose more online integrity framework info. • Coercive factors influence the disclosure by the Indonesian local authorities. • More enforcement is required to promote online integrity information in Malaysia. • Online integrity disclosure drives the attainment of sustainable development goal. [ABSTRACT FROM AUTHOR]

Abstract The development of irrigated agriculture is vital to nourish the burgeoning world population but without apposite drainage stipulations, this development can result in environmental problems of salinization and waterlogging in irrigated agro-systems. These problems of irrigated areas were generally assessed by conventional methods which demand a lot of data. The progress in computer technology has offered the ability to precisely simulate hydrologic and agricultural processes more readily than expensive and time-consuming field trials. This paper provides an overview of the applications of various computer-based mathematical models in managing the poor drainage-induced salinization and waterlogging problems of agricultural areas. The analysis of past literature revealed that a universally appropriate and all-purpose model is not available yet because each model has its advantages, disadvantages and limitations, and data requirements. The paper, first, presents an introduction of the salinization and drainage problems of agricultural areas along with the implication of the study which is followed by the background of the problems. Then the application of DRAINMOD and other computer-based models for solving the problems are detailed. It also deals with the integrated use of diverse models for managing the salinization problems. The relevant case studies pertaining to the applications of various mathematical models across the world are described and conclusions of the study are summed up. Graphical abstract Image Highlights • An overview of environmental problems of salinization and drainage is presented. • The rationale of the environmental problems of irrigated areas is provided. • The use of DRAINMOD and diverse models for solving the problems is detailed. • The integrated use of diverse models for managing the problems is discussed. • Case studies of uses of diverse mathematical models across the world are described. [ABSTRACT FROM AUTHOR]

Pumped hydro energy storage (PHES) has made significant contribution to the electric industry. Towards the improvement of this energy storage technology, a novel concept, known as gravity energy storage, is under development. This paper addresses the dynamic modeling of this storage system. A mathematical model is needed for descripting the hydraulic components of gravity storage as they include various time variant parameters. The objective of this paper is to build a robust model that simulates the dynamics of gravity storage system. This work concentrates on the hydraulic dynamics of the system rather than investigating the dynamics of the mechanical equipment such as turbine, and synchronous machine. The proposed model has been implemented in Matlab/Simulink, and demonstrated by a case study. The dynamic simulation is carried out to gain insight into the performance of the system. The model can predict the volume and the pressure of both chambers, as well as the piston motion throughout the charging and the discharging of the storage system. [ABSTRACT FROM AUTHOR]

Tackling societal challenges relating to sustainability requires both an understanding of the underlying complex socio-ecological systems and participation of scientists as well as relevant stakeholders, such as practice experts, decision makers, and citizens. This paper introduces the Decision Theatre Triangle, a method which combines empirical information, mathematical modelling and simulation, and a format for dialogue between scientists and stakeholders. While it builds on previous Decision Theatre work, the new structuring into these three elements emphasizes what is needed for setting up a Decision Theatre for a given challenge. Based on experience with a specific example – sustainable mobility in Germany – it is argued that agent-based models are particularly suitable for Decision Theatres and that the method is useful not only for decision support but also for science communication and co-creation of a deeper knowledge of the system under discussion. As a step towards facilitating a broader use of the Decision Theatre Triangle method, the paper then sketches research needs for each of its three elements, with a focus on mathematical modelling and simulation. [Display omitted] • The Decision Theatre Triangle combines data, models, and stakeholder dialogues. • It enables decision support, science communication and co-production of research. • Agent-based modelling shows benefits in the Decision Theatre Triangle method. • Setting up Decision Theatre Triangles for societal challenges needs model structures. [ABSTRACT FROM AUTHOR]

The production of mixed municipal waste changes due to the increase of separation rate, urbanization and other factors. The future changes in the legislation and technology development influences the way the waste is being treated. Thus the method, location and capacity of processing sites are unknown. The realization of future projects can be supported by the developing of transportation infrastructure. Such a feature may be represented by a robust transfer station grid, which can be designed to handle all possible future realizations and technological solutions (establishment of waste treatment facilities). The paper presents an approach utilising a mathematical model for the design of transfer stations. It is formulated as a multi-objective two-stage mixed-integer stochastic programming problem, where the trade-off between the environmental aspect and the economic viability is considered. The model is tested through a case study for the Czech Republic, where the waste treatment of over 6,000 municipalities is analysed. The solutions for different preferences are assessed throughout the principle called out-of-sample stability with 10,000 scenarios. The optimal decision consists of the robust transfer station grid with selected locations and their respective capacity. The particular solution with respect to the potential trade-off suggests to save 1.148 mil of travelled kilometres with only 0.77 mil EUR. The output in the form of decision support can serve possible stakeholders from the field of waste management to plan more sustainable projects. • A transfer station grid designed to handle future realizations and developments. • The efficiency of waste transport was analysed for more than 6000 municipalities. • A trade-off between environmental aspects and the economic viability was considered. • A solution suggests to save travelled 1.148 mil km with only extra 0.77 mil EUR. • Introduction. [ABSTRACT FROM AUTHOR]

In response to global warming, it is urgent to control and reduce greenhouse gas (GHG) emissions, especially from the supply chain perspective. The most often discussed topic in this domain indicates that emission trading scheme (ETS) could be employed as one of policy instruments for supply chain emissions management. Via mathematical models, scholars have shown that the employment of emission trading is affecting supply chain performances (both environmental and economic) in different levels. However, previous literature focus on the cost-effectiveness analysis only from the mathematical aspect. To provide policy-makers and companies with the theoretical bases on this hot topic, it is significant to discuss how ETS, one of market-based instruments, could be imposed in the context of supply chain from the mechanical point of view. By incorporating ideas from relevant literature, this paper generates two concepts/modes in imposing ETS on supply chain: jointly imposed supply chain emission trading (e.g., jointly imposed SC-ETS) and separately imposed supply chain emission trading (e.g., separately imposed SC-ETS). It illustrates the working principles of both concepts/modes and conducts a sandbox example to analyze the cost-effectiveness of them. Furthermore, this paper discusses the challenges and opportunities of implementing two modes from practical aspects. Results of quantitative analysis and discussion show that for the sake of both policy-makers and supply chain companies, the separately imposed SC-ETS allowing selling permits would be so far the better mode to manage supply chain GHG emissions compared to the jointly imposed SC-ETS. [ABSTRACT FROM AUTHOR]

This paper examines manufacturer manufacturing/remanufacturing planning issues in which a downward substitution strategy is applied between new and remanufactured products and presents three mathematical models to determine the optimal production quantities of a new and remanufactured product that maximize the total profits when considering capital and/or carbon emission constraints. These models include sales revenues, manufacturing/remanufacturing costs and revenue from or cost of carbon credit trading. Finally, four numerical examples are provided to explore the comparison results for the optimal manufacturing/remanufacturing decisions, total profits and carbon emissions as well as to analyze the impact of parameters under different constraints, such as the initial capital, carbon cap and carbon price on the optimal production policies. The results indicate that the capital constraint can encourage the manufacturer to remanufacture used products at a higher quality level and significantly reduce carbon emissions. However, the carbon emission constraint can always encourage the capital-constrained manufacturer to produce more remanufactured products to achieve maximum profit. In addition, it is found that the manufacturer need more capital to achieve the maximum profit when the carbon emission constraint is considered. Furthermore, when the capital constraint is considered, the carbon emission constraint will have more distinct influences on the production policies of the manufacturer. Finally, the results proposed in this paper provide applicable suggestions to manufacturers and policy-makers. [ABSTRACT FROM AUTHOR]

In this paper, an improved mathematical model is proposed to solve the multi-echelon biomass supply chain synthesis problem, including processing hubs selection, biomass allocation design and transportation mode selection, with the consideration of vehicle capacity constraint (weight and volume). On top of that, carbon emission penalty is introduced in the model in order to evaluate the environmental impact in the supply chain. The entire problem is modelled through mixed integer non-linear programming with the aim of maximising the overall profit, at the same time ensuring the minimal CO 2 emission. A comparative study between the model developed in the previous work (vehicle capacity constraint and environmental performance are not considered) and the current improved model is carried out to compare the reliability of the outcomes. Both models are illustrated by using a same case study in Johor, Malaysia. In order to fill the gap of lacking user-friendly decision-making tool for the transportation design in supply chain management, a novel graphical decision-making tool, called smart vehicle selection diagram is proposed in this paper. The diagrams are constructed based on the optimised results obtained from the formulated model. The user manual for the proposed decision-making tool is given in this paper. Besides, five sets of sensitivity analysis are conducted to identify the sensitivity of the assumed realistic factors (i.e. terrain profile, weather changes, traffic congestion, fuel price fluctuation and individual environmental preference) to the optimal results obtained from the proposed tools. This paper shows the potential of the proposed tools in providing rigid optimal solution for the proposed research problem. Finally, several potential future works is suggested in this paper to fill up some of the remaining research gaps. [ABSTRACT FROM AUTHOR]

Effective environmental management within companies, integrated with other management areas like quality and occupational health and safety, is nowadays assumed to be a strategic way to implement and improve lean and cleaner production. Also, sustainable development (SD) and business sustainability can be achieved through a better coordinated management of processes versus associated resources. This paper presents an in depth discussion regarding the promotion of integrated management systems, their benefits and major contribution towards the sustainable development of cleaner production related features. It addresses issues regarding the contributions resulting from the integration of standardized Management System (MS) from both internal and external perspectives. Complementing the overall review of aspects to the development of integrated management systems a survey was conducted in order to better understand the relevance of the identified success factors. The main findings in this paper are as follows: a contextualization model of sustainable development and integrated management systems considering the Triple Bottom Line: economic, social and environmental; and, a method and associated model to support the development of integrated management systems as well as general guidelines to support integration. It can be concluded that a proactive approach and commitment to cleaner production, supported by an integrated management system, brings relevant savings for organizations as well as providing value to the relevant interested parties. [ABSTRACT FROM AUTHOR]

Abstract Given the high variability of both quantity and condition of the returns, closed-loop supply chains depend on a mix of remanufactured and new components. Effectively managing the combined flow of returned and new components is imperative to minimize total system costs. This paper proposes a model that helps manage the flow of returns by determining the incentives to offer returners, while simultaneously determining a capacity contract with the supplier of new components. The model considers returns from multiple sources, where each source has different characteristics in terms of the quantity and condition of its returns. The model also accounts for uncertainties from the return sources, as well as the new components supplier. Such uncertainties result in a failure to meet the demand for components, incurring loss costs. Sensitivity analyses of a numerical example were conducted to illustrate the model and gain further insights. The results demonstrate noteworthy relationships between supplier-related costs and those associated with not meeting the required demand, as well as their influence on the incentives to offer and the supplier's capacity contract. Highlights • Components can be sourced new or remanufactured from multiple return sources. • Model determines the capacity to contract from the new component supplier. • Model determines the optimal incentive for each return source. • Costs include losses due to a lack of remanufactured components. • Major interactions exist among incentives, contract capacity and loss costs. [ABSTRACT FROM AUTHOR]

Abstract By the urban growth in the societies, water distribution systems have been particularly noteworthy. Regional water authorities face a wide range of decisions related to development and replacement of water distribution systems. In this context, decisions about pipe expansion, replacement, and material selection are some of the most important decisions because they have long-term effects and it is costly and difficult to change them. In this paper, a multi-objective mathematical model is constructed based on the needs of a regional water authority and is verified by its experts. The proposed model considers environmental and health considerations in addition to costs of purchasing and installing pipes. In order to cope with uncertainties in the parameters of the model, several robust counterparts have been proposed that takes into account various types of uncertainties. The proposed models have been implemented in a case study to show their applicability and usefulness in practice. Finally, a comparison is carried out between the corresponding results. One of the proposed robust models is suggested which considers all possible uncertainties and also holds the second position in providing reasonable objective values. This research helps the decision makers in pipeline expansion and replacement projects by proposing appropriate pipe materials regarding cost, health, and environmental aspects of candidate materials even under different uncertainties. Highlights • A new optimization model is proposed for pipeline expansion & replacement decisions. • The proposed model determines the optimal material for each location of pipeline network. • Besides piping costs, environment aspects and health-related costs are also considered. • Several robust optimization counterparts are proposed for coping with possible uncertainties. • The applicability and usefulness of all proposed models is tested in a case study. [ABSTRACT FROM AUTHOR]

Abstract The negative appraisals of the impact of airline industry on climate change have forced the industry to become greener. Over the past several decades, CO 2 emissions in the airline industry have increased considerably, thereby adversely affecting the environment. Therefore, airlines are seeking different approaches to reduce the environmental degradation. In this paper, we study cruise speed control to achieve this goal by reducing CO 2 emissions while studying passenger service level. We use some indicators to measure the passenger service level in the airline industry. These indicators create a conflict between CO 2 emissions and passenger service level. We develop a bi-objective mixed-integer non-linear programming model to integrate flight scheduling, aircraft-path assignment, and gate assignment with the aim of reducing CO 2 emissions while increasing passenger service level. Based on a real problem, the model can lead to 11% and 31% improvement in CO 2 emissions and passenger service level, respectively. The model is NP-hard. Therefore, we develop a new constructive heuristic method, and we also use the multi-objective simulated annealing algorithm and extend this algorithm to enhance its performance. We also use the design of experiment and Taguchi method to optimize the algorithms parameters. Finally, we evaluate the proposed methods based on information retrieved from major U.S. airlines. [ABSTRACT FROM AUTHOR]

Abstract The steel industry has faced challenges with regard to the raw materials and fuels and hence economic and environmental restrictions. This paper is focused on searching alternatives based on biomass and gaseous fuels suitable for replacing the coke breeze fossil fuel. Nevertheless, testing these technologies are expensive. Therefore, comprehensive mathematical models based on transport phenomena are efficient tools to study and indicate new possibilities for designing operational conditions as well as resizing the machines for minimizing the hazardous emissions. We proposed new concept of operation combining gaseous fuels and biomass for partially replacing the coke breeze in a compact sintering machine. Thus three possible ways for 20% of the amount of coke breeze replacement are analyzed in a combined manner: a) replacement by steelmaking mixing gas, b) replacement by biogas and c) replacement by pellets of biomass. The results indicated that about 20% of the solid fossil fuels could be replaced by waste solid residue of biomass (processed as small pellets). For the analyzed cases, the productivity increase of 5% for the steelmaking mixing gas, 15% for the biomass pellets and 25% for the biogas fuel. For all cases considered it was predicted a decrease of the amount of hazardous compounds emissions. Highlights • Actual specific consumption of coke breeze is 45 kg per ton of sinter. • Newly concept of the compact machine reduces up to 20% of the coke breeze. • Possible use of waste biomass and steelmaking gaseous fuels. [ABSTRACT FROM AUTHOR]

Different standards drive organizations to use energy more efficiently. ISO 50001 provides a basis for energy management improvement. The energy management standards represent a good practice, but they are not the best energy performance models. Energy maturity models help achieve superior performance. The paper proposes a new ISO 50001-based energy management maturity model which links ISO 50001 processes and Capability Maturity Model Integration criteria. The paper presents organizations that surpass ISO 50001 certification requirements, reaching higher maturity levels. A knowledge base that has been founded on the ISO 50001 processes, Plan-Do-Check-Act cycle and Capability Maturity Model Integration criteria, represents a novelty and a real contribution of the paper. This knowledge base contributes to better understanding and implementing energy management system, since it shows the relationship between the ISO 50001, which is an example of good practice in the energy management system implementation; the Plan-Do-Check-Act cycle, which underpins all the standards for systems management; and Capability Maturity Model Integration criteria, which can be associated with certain phases of the energy management systems development as shown in literature. The model for assessing the maturity of the energy management system utilizes a combination of different management concepts, which has not been displayed in the literature so far. The model was validated through its application in ISO 50001 certified and non-certified organizations and its validation shows that all maturity levels exist in practice. The model is universal and can be applied in manufacturing, as well as in service sectors. For ISO 50001 non-certified organizations there is a wide spread of results, while ISO 50001 certified organizations' results reveal consistency. The obtained results can be used as the reference for benchmarking studies in different industries and different countries. The proposed model can serve as a basis for national awards for energy excellence, applicable in Serbia and other countries. [ABSTRACT FROM AUTHOR]

Carbon reduction has become one of the most significant challenges for economic growth. This paper presents the preliminary analysis of undesirable output reduction targets and emission schedules in temporal–spatial comparisons based on Data Envelopment Analysis. The reduction targets of undesirable outputs are investigated, including the maximum, input, technical and ideal reduction targets. Four Data Envelopment Analysis models that are based on a sequential benchmark technology and variable returns to scale are introduced to measure these reduction percentages. In order to formulate the optimal emission schedule of undesirable outputs, an optimal model is provided without inflation. Data from the Australian construction industry from 2000 to 2010 are employed to develop the models. The results of the analysis indicate that the Australian Government could achieve its promised carbon reduction targets in the construction industry. Most Australian regions' construction industries possess carbon mitigation potential and some of them could increase their desirable outputs if carbon were decreased. This paper suggests that policymakers can benefit from formulating various suitable undesirable output reduction objectives and schedules through the models developed. The research method can be replicated for other sectors and regions focussing on undesirable output reduction. [ABSTRACT FROM AUTHOR]

The importance of integrating resources criticality assessment into Life Cycle Assessment (LCA) under the Life Cycle Sustainability Assessment (LCSA) framework has been discussed for some time. However, the question how to proceed towards integration remain unclear. Only very few work is published on this issue and to our knowledge only Schneider et al. (2014) have developed one operational model. In this paper we review existing literature critically and explain why integration is important and how it could be done, using knowledge from outside the LCA field. The criticality assessment method proposed by Graedel et al. (2012) is identified as the best starting point. This paper shows based on a critical review why bridging towards such a method could help addressing criticality in LCSA, what are possible options and which research needs exists. It reveals that currently LCA does not adequately cover resource criticality and that methods like Graedel et al. (2012) are inspiring further development of LCA; both approaches have a complementary nature and hence could be developed towards integration within the LCSA framework. Currently resource indicators are not meaningful in LCA, wherefore there is no consensus in LCA community on what to recommend; hence the Area of Protection Natural Resources needs to be rethought. Broadening the scope of LCA towards LCSA provides a conceptual framework to keep LCA relevant for assessing sustainability challenges like access to resources. [ABSTRACT FROM AUTHOR]

In this paper, we propose an original double flexible job-shop scheduling problem (DFJSP), in which both workers and machines are flexible. Because of the characteristics of double flexibility, DFJSP conforms to practical production better than the flexible job-shop scheduling problem (FJSP). In addition, a multi-objective optimization mathematic model according to the DFJSP is proposed, which is concerned with the processing time indicator that is usually optimized by most existing studies; green production indicators, namely, factors regarding environmental protection; and human factor indicators, which are actual indispensable elements that exist in the production system. Furthermore, ten benchmarks of DFJSP are presented and solved using a newly proposed hybrid genetic algorithm (NHGA). With the proposed NHGA, a new well-designed three-layer chromosome encoding method and some effective crossover and mutation operators are developed. To obtain the best combination of key parameters in NHGA, the Taguchi design of experiment method is used for their evaluation. Finally, comparisons between NHGA and NSGA-II show that the proposed NHGA has advantages in terms of the solving accuracy and efficiency of the DFJSP, particularly at a large scale. It would be beneficial to apply our proposed model to the multi-objective optimization of scheduling problems, especially those considering human factor and green production-related indicators. [ABSTRACT FROM AUTHOR]

With the rapid development of the sharing economy, outsourcing logistics operations to third party logistics has become an efficient way of reducing costs in freight transportation. It can be modeled as a variant of the open vehicle routing problem (OVRP), where the vehicles do not return to the depot after servicing customers. However, very few papers have studied fuel consumption in the context of third party logistics. In this work, the mathematical model of the green open vehicle routing problem with time windows (GOVRPTW) was described based on the comprehensive modal emission model (CMEM). A hybrid tabu search algorithm involving several neighborhood search strategies was designed to solve this problem. Computational experiments were performed on realistic instances based on the real road conditions of Beijing, China. The effect of empty kilometers is analyzed through comparing different cost components. Compared with closed routes, the open routes reduced the total cost by 20% with both the fuel emissions costs and the CO 2 emissions cost down by nearly 30%. For the experiments with congested nodes, the fuel and emissions cost rose by 12.3%, and the driver cost even increased by 31.3%. [ABSTRACT FROM AUTHOR]

The so-called Paris Agreement, signed by 195 countries, has led to the setting of some ambitious target reductions in greenhouse gas emissions by most developed countries. The over-arching goal of those reduction targets is to limit global warming to less than 2 o C compared to pre-industrial levels. Yet, despite these commitments from the highest governance levels, there is still no deterministic model on how these national target reductions will be cascaded down to the commercial sector, which accounts for the lion's share of these emissions. In this paper, we present a novel framework which enables the setting, measurement and tracking of the emissions performance of every commercial entity based on a single metric. We further present empirical evidence from the automotive industry to illustrate how the model helps to readily identify the low versus high performers. The model also reveals one car company that stands out as the industry benchmark by already exceeding the performance required by the 2025 emissions target set by the US. The model proves successful in achieving the objectives of being: science-based, goal-driven, equitable, comparable and actionable, and as such can be readily used to accurately compare competitors from the same industry and provide the basis of a more equitable, performance-based carbon tax market, as well as the ability to assess accurately how well a specific country is meeting its reduction quota and how the various industry sectors are impacting that goal. [ABSTRACT FROM AUTHOR]

Returning of biomass ash as fertilizer to field plays great role in sustainable utilization of biomass as energy. In the fertilizer application, release rate of nutrients from ash should be controlled to avoid nutrients shock to plants. Making ash into briquettes (granulated ash, pellet, tablet) is a good choice to slow down the release rate of nutrients and prevent dust formation. However, experimental or theoretical analysis of the release behavior of nutrient from ash briquette is scarce. In this paper, different sizes (from Ф6 mm × 2 mm to Ф15 mm × 5 mm) of tablets of biomass ash were made and their nutrient release behavior was investigated experimentally. Results showed that the release rate of potassium in tablet ash was about 1/20-1/60 of that in the powder ash. And that changing tablet size in the normal size range could not decrease the nutrient release rate to the value required by the norm for slow-release fertilizer. Based on the experiments, the mathematical description of the nutrients release process was established and a Matlab code was written for modelling. The theoretical model was validated and parameters required to make slow release fertilizer from the ash were predicted. It showed that, in order to produce slow release potassic fertilizer, much bigger tablet size (from Ф15 mm × 5 mm to Ф210 mm × 70 mm), much lower saturated concentration (from 0.17 to 0.17/14 2 kg/kg water for potassium), or much smaller effective diffusion coefficient (from 3.2 × 10 −10 to 1.6 × 10 −12 ) are necessary. The theoretical model can be generalized to describe the release behavior of any nutrient and can be used in the parameters optimization for producing slow/control-release fertilizer. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical model to determine the minimum energy targets for a batch process with flexible schedule. Techniques developed for flexible-schedule batch processes typically result in nonlinear formulations. The proposed model was formulated as a mixed integer linear programming model (MILP). The model is developed based on the source-demand classification of process streams instead of the typical classification of hot and cold streams. In such classification, each stream is simultaneously treated as a source at its shifted supply temperature, and as a demand at its shifted target temperature. Such classification eliminates the model's non-linearity and reduces its complexity as well as the solution time. The mathematical model can be used to calculate the utility targets for a flexible-schedule batch process. Application of the proposed mathematical formulation demonstrates significant energy saving potential. The first illustrative example predicted a potential reduction of 11% cold utility and 14% hot utility. In the second illustrative example, up to 35% hot utility reduction and 62% cold utility reduction could be achieved. [ABSTRACT FROM AUTHOR]

This paper proposes a mathematical model and two heuristic procedures to solve the cutting stock problem with usable leftovers, relating the implications of the model with aspects considering sustainability in terms of environmental, economic and social issues. The possibility of generating leftovers that can be used or sold, reduces raw material waste during the cutting process and, consequently, increases companies’ profits. By reducing waste and increasing profits, companies can become more competitive in the market. They can also integrate environmental aspects into their operational strategies and, therefore, create a better self-image and profitability, generating more jobs and contributing to a stronger local economy. We believe that the model is more likely to be adopted by smaller companies, which generally face numerous barriers but at the same time have a significant social impact, generating income and jobs. Based on the knowledge of the authors, this is the first study that relates a cutting problem with its implications for sustainability. Computational tests were performed, and the obtained results are discussed considering the win-win approach to sustainability. [ABSTRACT FROM AUTHOR]

In this paper, we develop a decisional framework and a mathematical model for the sustainable design of biodiesel supply chain networks (BSCND). We consider a broad group of sustainable aims, i.e. standard economic goals (revenue and logistics costs of BSCND), environmental issues based on a biodiesel production life cycle assessment (LCA), and the social incidental aspects (e.g. crime control, political stability, and community attitude, among others). The framework begins with a simulation of the biodiesel production system, feeding later, with suitable input parameters and suitable solutions, and a macro-location model designed to establish the regional positioning of biofuel conversion plants. Optimal regions are used as initial feasible solution space for the proposed micro-location model. In this part of the framework, we introduce an adaptation of Extended Goal Programming to rank the best municipalities (definitive locations) emphasizing the social aspects under consideration. The framework application is set up in the following Colombian context: first generation biodiesel production from palm oil feedstock. Our computational results indicate that the Colombian city of Rionegro (in the Santader region) is the most sustainable location for a new biodiesel plant. [ABSTRACT FROM AUTHOR]

The cold chains prevent perishable products from decay, but are highly energy-intensive. As much as 15% of total worldwide energy already fuels cold chains infrastructures and since 40% of food deliveries would need refrigeration, the growth of global food demand and of the widening of the global supply chains will enormously increase the energy request and the associated carbon emissions. The environmental temperature has indeed a clear effect on the performance of the cold chain, and the interaction between climate and the distribution of perishable products cannot be ignored. In this paper a mixed-integer linear programming model for the planning of the production, storage and distribution operations of perishable products which incorporates the interactions with the weather conditions is formulated. This addresses an open field of research, which is still uncovered. The proposed model has been applied to an illustrative case study of a cold chain for cherries, that demonstrates the influence of the weather conditions on the energy costs for the products refrigeration on vehicles during transportation and at the warehouse during storage. Successful control of the distribution operations according to the weather conditions can result in significant reduction of energy consumption and costs, which increase indeed with the raise of environmental temperatures and stresses. Based on the results obtained in this study, these costs are not handled by the extant operations planning models, and their minimization can lead to significant economic and environmental savings for the cold chain. [ABSTRACT FROM AUTHOR]

This paper reviews concentration potential concepts and their applications in the design of water-using networks (WUNs) with multiple contaminants. The concentration potential concepts were proposed to determine the concentration order of water streams of multiple contaminants based on the overall allocating possibility of source streams to demand streams on the analogy of single contaminant WUNs. The precedence order of water-using processes, which is crucial for the network design, can be effectively identified by the values of Concentration Potential of Demands (CPDs). The concentration potential concepts, which were originally presented for the water networks of fixed contaminant load model, up to now have been successfully used to design a verity of water-using networks. Computing software has also been developed by combining the concentration potential concepts and linear programming approach. The methods proposed based on the concentration potential concepts have the advantages of simple calculation and clear engineering meaning. The results obtained based on the concentration potential concepts are comparable to that obtained by the literature methods. It is shown that the concentration potential concepts are powerful tools for the design of WUNs with multiple contaminants. [ABSTRACT FROM AUTHOR]

Understanding spatiotemporal urbanization is one of the key questions related to sustainable urbanization in the drylands of northern China (DNC). However, urban expansion in the DNC has not been quantified and assessed effectively due to a lack of reliable data and methods. In this paper, we investigate urban expansion in the DNC at multiple scales, ranging from the whole region to four dryland subtypes, and six urban agglomerations in the DNC from 1992 to 2015. We also simulate urban expansion in the DNC from 2015 to 2050 by coupling the scenario framework of the Shared Socioeconomic Pathways (SSPs) with the Land Use Scenario Dynamics-urban (LUSD-urban) model. Despite of the uncertainty in the research, our findings provide useful insight into the past and the future urban expansion in the DNC. The results indicate that the urban land in the DNC expanded rapidly from 4110 km 2 in 1992 to 20,969 km 2 in 2015. Furthermore, the urban land in the DNC will continue to expand from 20,969 km 2 to 22,987–36,622 km 2 by 2040, with an annual growth of 80.72–403.48 km 2 under all SSPs. Thus, it is suggested that effective measures are urgently needed to facilitate sustainable urban development in the DNC. [ABSTRACT FROM AUTHOR]

Hybrid flowshop scheduling problem is a hot research topic, and is widely applied for production shop or line in chemical industry, metallurgical industry, semiconductor manufacturing and other industries. However, on the one hand, the uncertain events are inevitable in actual production, which will disrupt the production plan. On the other hand, nowadays the energy problem becomes more and more serious, and attracts much attention in the manufacturing industry. Therefore, an energy-efficient hybrid flowshop rescheduling problem under the machine breakdown is addressed in this paper. Firstly, the mathematical model for the problem is established, and an energy saving strategy based on problem model is designed, which can ensure the reduction of energy consumption without affecting the production efficiency. Then, an improved multi-objective firefly algorithm is proposed to optimize the production efficiency, energy consumption and production stability. To express the problem characteristics, a two-level encoding mechanism is used to describe the individual, and a corresponding decoding mechanism is presented to generate the scheduling scheme. By simulating the location updating law of the fireflies, the population updating rule is designed, in which the variable neighborhood search is employed to avoid the local optimal. To ensure the quality of the solution set, the fast non-dominated sorting method and elite individual reserving strategy are introduced to the population evolution. Finally, the numerical experimental results indicate that the designed energy saving strategy is effective, and the proposed algorithm obtains better Pareto frontier and performs the better convergence and diversity comparing with MOEA/D and NSGA-Ⅱ, the common algorithms to solve complex multi-objective optimization problem. • A multi-objective energy-efficient hybrid flowshop rescheduling problem is studied. • The problem characteristics of dynamic event and energy consumption are analyzed. • An improved multi-objective firefly algorithm is proposed and tested by experiments. • An energy saving strategy based on the processing speed selection is designed. • The total energy consumption is reduced without affecting the production efficiency. [ABSTRACT FROM AUTHOR]

Water conservancy project bidding involves many aspects including nature, society, economy, and environment. In water conservancy project bidding evaluation, both quantitative and qualitative indexes are involved; moreover, different targets are often incommensurable and compete with each other. Scientific decision-making in bidding evaluation is key to linking the stages of project bidding; selecting an appropriate contractor is not only conducive to improving the project quality, but also helpful to achieve the goal of saving on investments. This paper intends to study the problem of multi-target group decision-making in project bidding processes via the use of the mathematical method of fuzzy clustering. Bidder 3 is finally chosen as the most suitable contractor for the construction of this project by determining the score matrix and index weight vector of the four bidders concerned. Results have indicated that the aforementioned method is more reasonable and reliable; thus, the bidding evaluation decision is more scientific. [ABSTRACT FROM AUTHOR]

Combustion of fossil fuels in the transport sector represents the second largest source of greenhouse gas emissions. For this reason, governments are fostering diversification of energy sources by creating a set of governmental environmental policies and initiatives. In this context, biofuels are expected to represent a substantial part of source diversification, but it is necessary to assess the sustainability of their market to explore its effect on economical, technological, social, political and environmental dimensions. This research presents a dynamic simulation modelling of the Colombian biodiesel market and analyzes the policy support instruments for creating and managing it. A system dynamics based model is proposed to enable decision-makers to understand the influences between the different variables that describe the system and the impact of the biodiesel government policy in Colombia. The primary focus of this paper is to establish the characteristics of each sustainability dimension for the case of study and apply the system dynamics methodology with different types of validation. Finally, the Colombian market status and a sensitivity analysis are developed. The results show that in order to support the development of this sector, it is necessary to diversify the raw materials for the production of biodiesel in the medium term, which means raw materials without competence for the primary rainforest or competition with food productive lands. [ABSTRACT FROM AUTHOR]

Environmental Sustainability is one of the ‘Grand Challenges’ for manufacturing success in the 21st century. The present article mainly focuses on energy use during the manufacturing steps used for assembling products. In particular, industry still needs systematic and reliable ways to capture information for ultimately accounting for energy efficiency in manufacturing processes. For that purpose, an information model in the form of a formal ontology was created using information elements as building blocks, which emerge from manufacturing process models, supply chain operations, manufacturing process parameters, 3D form features and exergy-based thermodynamic analysis. These information elements were integrated by means of semantic relationships in an ontology. Once this information model was constructed, an application example of a welded hull panel assembly was used for verification of the model's representativeness and completeness. Results show that it is feasible to correlate all required data by means of semantic relationships for estimating energy efficiency indicators prior to physical prototyping, or ultimately comparing different alternatives for manufacturing processes regarding energy efficiency. However, manufacturing processes must be described in detail in order to allow energy efficiency analyses. In addition, geometric models need to be able to represent form features that can best relate to specific manufacturing process parameters. And finally, energy efficiency indicators, such as the degree-of-perfection can be derived from a comprehensive thermodynamic analysis, to be performed in each individual process step. Results indicate it is possible to provide an information structure for the calculation of the degree-of- perfection associated with an exergy-based thermodynamic analysis in assembly processes. Therefore, it has the potential to serve as a basis for a unifying framework for developing software applications that could allow the calculation of the degree of perfection in manufacturing operations. In addition, the resulting information model may facilitate data integration in the extended enterprise environment as well as the development of standards that can lead to seamless interoperability of manufacturing information systems. This paper presents the means by which energy efficiency can be accessed directly from an integrated semantic model, and opens the possibility to be extended for many different sorts of manufacturing processes. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hybrid BSC-DEA framework for performance evaluation in sustainable supply chains. The proposed DEA model is capable of dealing with both qualitative and quantitative indicators while accounting for desirable and undesirable indicators. A tailored network DEA model involving a set of comprehensive sustainability indicators is applied to rank different supply chains from sustainability viewpoint to find the efficient and benchmarked units at each echelon. Then, sustainability indicators are classified into four groups according to BSC perspectives to help policy makers and top managers to have a more comprehensive and thorough understanding of the sustainability with respect to the long- and short term strategies. Finally, a number of sensitivity analyses are performed to identify the effective factors and strengths and weaknesses of each supply chain are identified based on BSC perspectives. To demonstrate the capabilities of the proposed approach, this framework is implemented for performance evaluation of plastic recycling companies in Mazandaran and Golestan provinces of Iran and some helpful managerial insights are derived from the numerical results. [ABSTRACT FROM AUTHOR]

The study presented in this paper uses a mathematical model to measure the degree in which a product will be perceived as environmentally friendly from its physical attributes. A model based on genetic algorithms and neural networks was developed to predict the judgement of the users about environmental friendliness of different tables. Opinions of real users about a large set of tables were used to train the model. The results of the study suggest that, using this procedure in advanced stages of product design process, designers can determine the set of product's physical attributes that best convey the idea of “environmentally sustainable” to the customer. The analysis of the obtained model allows establishing how different product's attributes influence users' perception. From these results, the utilization of users' affective response models to design the appearance of environmentally sustainable products is discussed. [ABSTRACT FROM AUTHOR]

This paper presents a participatory process, in the course of which stakeholders identified an implementable strategy for promoting renewable electricity generation in a county in Germany. In the process, a new combination of participatory methods was applied, including two participatory modeling approaches that are based on causal networks and the participatory development of qualitative normative scenarios. After the participatory process the combination of methods was evaluated regarding the ability to 1) map out the diversity of stakeholders' perspectives, 2) to grasp the complexity of the problem, 3) to make uncertainty of complex problems transparent and 4) to support the identification of implementable strategies. Evaluation results showed that the applied methods were able to fulfill criteria 1) to 3). Specifically, application of actor modeling lead to fulfillment of criteria 1) and 2), while normative scenario generation addressed criterion 3). Criterion 4) was only partly fulfilled due to lack of credibility of the Bayesian Network modeling results. This was caused by the high uncertainty of the conditional probabilities elicited from experts, as there is little empirical system knowledge in particular about the potential effects of management options. On the other hand, stakeholders were not sufficiently involved in the construction and application of Bayesian Network models during the participatory process. [ABSTRACT FROM AUTHOR]

The amount of material entering end-of-life vehicles (ELVs) management systems all over the EU has been reduced due to increased export of used vehicles to non-EU countries. According to the latest data, only 6.23 million ELVs were processed in 2012 (e.g., 8.37 million ELVs were processed in 2009). Considering that currently 342 active vehicle recycling factories exist in the EU, as well as that in the last ten years the total processing capacity has been increased several times, it is clear that there is a serious conflict. This paper proposes a multi-stage interval-stochastic programming model for planning end-of-life vehicles allocation. The developed model is able to reflect dynamics in terms of decisions for ELV allocation from a multi-region waste management system to multiple vehicle recycling factories within a multi-period context. It is capable of incorporating multiple policies within the optimization framework. Uncertainties expressed as probability distributions and discrete intervals are effectively handled, based on a multi-layered scenario tree with a finite set of scenarios. A semi-hypothetical case study is conducted in order to demonstrate the potentials and applicability of the proposed model. Influences of parameter uncertainty on model solutions are thoroughly examined. Comprehensive analyses of various policy situations, associated with different levels of economic penalties and system failure risks, are presented. The proposed model is effective for solving difficult ELV allocation problems with uncertainties included as part of the formulation. It can help quantify the relationships between ELV management system profit and disruption risk of the vehicle recycling factories, and thus provide optimal ELV allocation schemes. [ABSTRACT FROM AUTHOR]

Sustainable procurement is the process of meeting the needs of an organisation with the most beneficial monetary value, while mitigating the diverse effects of its operations on society and environment. There are studies which adopt environmental criteria to procurement decisions, whereas, works integrating the three dimensions and discussing the trade-offs between them are scarce. In this paper, the three dimensions of corporate sustainability; environmental–economical–social, are integrated into supplier selection and demand allocation decisions. With their integrated approach, the proposed mathematical models aim to contribute to the relevant literature by analysing different sustainable procurement strategies. Initially a questionnaire is introduced for measuring the sustainability scores of a company's potential suppliers, and these scores are then used as an input to the models. The developed mixed-integer linear programming models distribute demand to the most sustainable firms in the supplier pool of the company, while ensuring minimum procurement cost for the identified strategy. The questionnaire and models are implemented in three companies to interpret the outcomes of different sustainability strategies on the procurement decisions. Selection of the most appropriate strategy is a managerial decision influenced by the varying dynamics of the company and the market conditions. These models demonstrate an easy and practical approach in assisting sustainable procurement. Results are promising in displaying the trade-offs between the sustainability dimensions of different strategies with alternating procurement costs, and can aid the managers to integrate environmental, economical, and social aspects into their supply chain operations. [ABSTRACT FROM AUTHOR]

Generally, industry includes various sectors like manufacturing, energy, materials & mining, and transportation. Industry consumes about one half of the world's total delivered energy, and manufacturing is one of the energy-intensive industrial sectors. With the rising energy price, the energy cost is becoming a controllable expenditure in manufacturing. In this paper, a generic method has been proposed to minimize the energy cost and improve the energy efficiency of manufacturing unit processes. Finite state machines have been used to build the transitional state-based energy model of a single machine. A mixed-integer linear programming mathematical model has been formulated for energy-cost-aware job order scheduling on a single machine. A generic algorithm has been implemented to search for an energy-cost-effective schedule at volatile energy prices with the constraint of due dates. As a result, plant managers can have an energy-cost-effective job order schedule which is associated with machine energy states along time, and can also get time-indexed energy simulation of the schedule. In comparison to most of the static scheduling approaches, stochasticity has been further handled through a cyclic interaction between the scheduler and the energy model, which facilitates to investigate how stochasticity on a shop floor affects the performance of energy-cost-aware scheduling. Empirical data have been used in the case study, including the power measured from a grinding machine, and the real-time pricing and time-of-use pricing tariffs. The proposed method has been demonstrated to be both energy-efficient and energy-cost-efficient even at the presence of stochasticity. As a joint effort of energy efficiency and demand response within demand side management, this method shows its effectiveness for contributing to the reduction of greenhouse gas emissions during peak periods, and for leading to energy-efficient, demand-responsive, and cost-effective manufacturing processes. [ABSTRACT FROM AUTHOR]

Electricity generated from forest-based biomass is an attractive source of renewable energy. However, the cost of generating heat and/or electricity from it is relatively high due to the low energy density of wood, high moisture content and variations in its quality and availability. Models have been developed to optimize the supply chain and reduce the cost per kilowatt hour generated. This paper focuses on incorporating uncertainty in the supply chain of such a model. The model considers the tactical supply chain planning of a power plant over a one-year time horizon with monthly time steps. Uncertain parameters which impact the net profit of the power plant include ‘biomass quality,’ namely moisture content and higher heating value, and ‘monthly available biomass’ from different suppliers. Robust optimization is used to model uncertainty in the quality of biomass. Then a hybrid, multi-stage, ‘stochastic programming-robust optimization’ model is presented in order to simultaneously include uncertainty in biomass quality and biomass availability. It is demonstrated that the hybrid model takes advantage of both modelling approaches to balance the profit estimates and the tractability to various circumstances. The model provides solution considering all instances of the uncertain parameters within the defined sets and scenario tree. The results revealed a major trade-off between profit and range of biomass quality. Profit decreased by up to 23% when there was ±13% variation in moisture content and ±5% change in higher heating value. The model achieved a biomass purchase cost that was lower than the current commercial costs at the power plant. Implementing the model could prevent production curtailment and undesirable fluctuation in storage levels which occurred in the past due to variations in biomass availability and quality. [ABSTRACT FROM AUTHOR]

Technology changes rapidly over years providing continuously more options for computer alternatives and making life easier for economic, intra-relation or any other transactions. However, the introduction of new technology “pushes” old Information and Communication Technology (ICT) products to non-use. E-waste is defined as the quantities of ICT products which are not in use and is bivariate function of the sold quantities, and the probability that specific computers quantity will be regarded as obsolete. In this paper, an e-waste generation model is presented, which is applied to the following regions: Western and Eastern Europe, Asia/Pacific, Japan/Australia/New Zealand, North and South America. Furthermore, cumulative computer sales were retrieved for selected countries of the regions so as to compute obsolete computer quantities. In order to provide robust results for the forecasted quantities, a selection of forecasting models, namely (i) Bass, (ii) Gompertz, (iii) Logistic, (iv) Trend model, (v) Level model, (vi) AutoRegressive Moving Average (ARMA), and (vii) Exponential Smoothing were applied, depicting for each country that model which would provide better results in terms of minimum error indices (Mean Absolute Error and Mean Square Error) for the in-sample estimation. As new technology does not diffuse in all the regions of the world with the same speed due to different socio-economic factors, the lifespan distribution, which provides the probability of a certain quantity of computers to be considered as obsolete, is not adequately modeled in the literature. The time horizon for the forecasted quantities is 2014–2030, while the results show a very sharp increase in the USA and United Kingdom, due to the fact of decreasing computer lifespan and increasing sales. [ABSTRACT FROM AUTHOR]

The blast furnace is the traditional ironmaking process for the production of hot metal with high iron content. The Corex ® and Finex ® processes are the main alternative technological solutions in this field of industrial activity. Their main advantages are focused in better economic and environmental characteristics. The melter gasifier is the most important unit operation of both processes. The aim of this paper is to describe the development and implementation of a predictive mathematical model of a multizone melter gasifier. The process modelling and simulation software used for this task is the gPROMS ModelBuilder. For the calculation of the hot metal/slag mixture chemistry, the Gibbs minimisation routines for multicomponent/multiphase systems were implemented through FactSage and ChemApp. A communication scheme between gPROMS and FactSage/ChemApp was established. The validation of this methodology took place by comparing the basic iron making reactions against literature. Special attention was given in the numerical stability by designing a dedicated initialisation strategy. The agreement between simulation results and plant data proved to be successful for the main components (iron, carbon, calcium oxide, magnesium oxide, aluminium oxide, sulphur). Deviation appeared for the silicon and manganese components. This work contributes in making accurate predictions for the hot metal and slag chemistry based on thermodynamic first principles. The reliable calculation presents the opportunity to apply rigorous optimisations that can lead to higher process efficiency. This reflects the potential of reducing fuel consumption, thus leading to lower environmental emissions. [ABSTRACT FROM AUTHOR]

Currently, more research to implement and monitor cleaner production practices for distribution and sustainable management of natural and alternative water sources to comply with the demands of the different users while preserving water levels are needed. In this paper, a periodic hourly-based model with meaningful parameters has been developed to analyze and forecast water demand as a function of time, thus enabling a better understanding of the consumption pattern and the condition of the pipe network. The model was tested by investigating the daily water consumption from selected categories of users which were isolated from different distribution networks in Sligo, Ireland. The flow data used was obtained in 15-min intervals and averaged in different time periods for analysis. In all cases, the model fittings obtained were highly consistent and all the parameters showed satisfactory confidence intervals ( α = 0.05), thus demonstrating the reliability of this approach. The model provides a quick analysis revealing the regularities of water demand that could benefit water utility managers and researchers: to obtain optimal regulation and pumping schemes; for planning and design purposes; to control unexpected scenarios that can take place during the distribution of water; the performance of water distribution systems; and to locate possible network failures. In addition, the model parameters can be used as standard criteria for water utilities to compare precisely the water demand between different areas, identify complex trends and analyze the pipe network for managing, auditing and monitoring purposes. [ABSTRACT FROM AUTHOR]

This paper presents a novel algebraic technique of supply network synthesis and analysis. A case study of biomass processing for supply network synthesis using three techniques (i) mathematical modelling (ii) supermatrix scoring concept and (iii) algebraic analysis with graphical visualisation is demonstrated. The results and performances of three techniques are compared. Comparable modelling results are obtained for all three approaches. The introduction of quantitative cum graphical analysis of supply network allows the performance overview of each possible choice of supply network in one picture. Besides, the algebraic method allows the concurrent set-up of material allocation and ranking of possible supply network choices. This outweighs the mathematical modelling technique that allows for optimal supply network synthesis but giving no insight to the performance of next network choices; and the supermatrix scoring technique that ranks the general supply network choices in a whole picture yet incapable to capture the optimal selection which involves only part of the players, especially in supply network problem. [ABSTRACT FROM AUTHOR]

Various environmental regulations put ever stringent requirements on the automotive industry as a part of solution to the problem of global warming and climate change. In Europe, the upcoming Euro 6 standard that will come into force on September 1, 2014 demands reduction in NO x emissions from cars and vehicles intended for transport by more than 50% compared to the current standard. The urea-water-solution (UWS) based selective catalytic reduction (SCR) is currently the most promising method for fulfilling these requirements. In principle, the UWS spray is injected into a hot exhaust gas stream preceding the SCR catalyst and ammonia is generated through series of chemical reactions. Then, the generated ammonia acts in various deNO x reactions as a reductant. This paper investigates application of numerical modeling in the area of environmentally friendly technology of mobile SCR as a green engineering measure to reduce pollution in the road transport sector. Within this work the mathematical model of surface tension has been developed and compared to analytical expression for isothermal droplet spreading. Furthermore, this model was incorporated into the wall film module of the commercial computational fluid dynamics code FIRE for description of urea-water-solution injection into hot exhaust gases of diesel engine and compared to experimental data. Results of the conducted numerical study support the feasibility of commercial application of the presented model. [ABSTRACT FROM AUTHOR]

In this paper, we present the development of a friction model as a function of the cutting speed and tool feed rate when machining with minimum quantity lubrication. A finite element model of the minimum quantity lubrication process is developed and simulated by considering the friction coefficient as a state variable. The tool-chip friction coefficients for different machining conditions are obtained through inverse modelling and presented as a mechanistic model. The validated model is utilized to understand the effects of machining conditions, temperature, and contact length of the tool-chip interface. [ABSTRACT FROM AUTHOR]

To reduce the negative impact of the conventional vehicles, governments and authorities try to provide facilities in order to encourage people to use electric vehicles. For this purpose, determining the location and the number of charging stations is of paramount importance. It becomes more challenging when some charging stations cannot provide service due to the disruption or breakdown. In this paper, a bi-objective mixed-integer linear mathematical model for a charging station location problem is developed and solved by Lagrangian relaxation method. Two different chargers that could be installed in the charging stations and budget constraint is considered in the model. To evaluate the applicability of the proposed model on real-world problems, a case study on Tehran is conducted. Based on computational experiments and numerical results, sensitivity analysis on key parameters of the problem is carried out and some helpful suggestions are presented for decision-makers. • A bi-objective region-based model for optimizing CSLP is presented. • Disruption in charging stations is taken into account. • Two different types of chargers and tolerable distance for the users are considered. • The proposed model is implemented in a real-world case study to evaluate the applicability of the model. • Lagrangian relaxation algorithm is used to solve the model and some useful managerial insights are also presented. [ABSTRACT FROM AUTHOR]

Safe and stable operation of hydropower plants is the basis and prerequisite of great importance for clean energy production and integration of renewables. To better analyze the operating stability of hydropower generating systems (HGSs), a novel frequency-domain method (global matrix method) is proposed in this paper. First, the principle of the new method and the mathematical models of each common hydraulic component in HGSs are presented. Second, three general steps for deriving the global matrix of an arbitrary system and order-reduction and numerical calculation of the matrix are illustrated in detail. In two case studies of HGS stability analysis, the transfer function method (TFM) suitable for time-frequency domain analysis is applied to evaluate the global matrix method. For simple single-unit system, the new method is compared by the TFM from both frequency domain and time domain. For complicated multi-unit system, the TFM is not applicable to the frequency-domain stability analysis, and only the time-domain simulation is applied to verify the new method. The results indicate that the stability regions by the two methods are in good agreement, verifying the accuracy of the new approach. The proposed method can replace the TFM for stability analysis of HGSs in frequency domain, outperforming the latter in applicability, flexibility, and quantification function. • A global matrix method for stability analysis of hydropower systems is proposed. • Order-reduction and numerical calculation of the global matrix are illustrated. • The accuracy of the novel method is verified by transfer function method (TFM). • Applicability, flexibility and quantification function are the main features. [ABSTRACT FROM AUTHOR]

This research presents an optimization problem associated with scheduling of unrelated parallel machines considering the simultaneous effects of start-time-related deterioration, position-related learning and sequence-related setup times, with the aim to achieve an optimized value for the mean weighted tardiness and power consumption minimization. A workaround is proposed and served as the converter for solving the Mixed Integer Programming (MIP) problem by the continuous-based metaheuristic algorithms. Knowing the NP-hard nature of the problem, three metaheuristic algorithms, namely, Genetic Algorithm (GA), Cat Swarm Optimization (CSO) and Interactive Artificial Bee Colony (IABC), are employed to obtain quality solutions within acceptable computation time. A unique elitism strategy is introduced in the conventional CSO to reduce the computational time of its seeking mode and to provide improved solution, with the new algorithm form called CSO-Elit. Furthermore, a compact solution expression form is proposed for the use of GA, CSO-Elit and IABC to reduce the number of constraints. With the newly proposed model, many essential constraints are automatically built into the solution representation. Accordingly, the efficiency of algorithms is compared with LINGO regarding the quality of solutions, computational time, and overall power consumption using two sets of problems in small and large scales. In solving the small-scale cases, no statistically meaningful difference was observed between LINGO, GA and CSO-Elit, while in large-scale instances CSO-Elit demonstrated higher performance. The contributions of this paper lie in modeling a complex parallel machines problem considering power consumption minimization and proposing a new form of CSO algorithm with elitism strategy to reduce the computational time. • A novel problem has been identified and explored in this paper. • The model includes mathematical modeling and optimization of an unrelated parallel machine scheduling problem. • Several restrictions which are practical and industrially relevant are considered in this paper. • A new metaheuristic approach by adopting an elitism strategy into a metaheuristic algorithm is proposed. [ABSTRACT FROM AUTHOR]

The COVID-19 virus in a short time has caused a terrible crisis that has been spread around the world. This crisis has affected human life in several dimensions, one of which is a sharp increase in urban waste. This increase in waste volume during the pandemic, in addition to the intense increase in costs associated with the risks of virus contagion through infectious waste. In this study, a hybrid mathematical modelling approach including a Bi-level programming model for infectious waste management has been proposed. At the higher level of the model, government decisions regarding the total costs related to infectious waste must be minimized. At this level, the collected infectious waste is converted into energy, the revenue of which is returned to the system. The lower level relates to the risks of virus contagion through infectious waste, which can be catastrophic if ignored. This study has considered the low, medium, high and very high prevalence scenarios as key parameters for the production of waste. In addition, the uncertainty in citizens' demand for waste collection was also included in the proposed model. The results showed that by energy production from waste during the COVID-19 pandemic, 34% of the total cost of collecting and transporting waste can be compensated. Finally, this paper obtained useful managerial insights using the data of Kermanshah city as a real case. [Display omitted] [ABSTRACT FROM AUTHOR]

The question about how to choose the best recycling policy is particularly relevant in developing countries. On the one hand, many of these countries have no national waste management strategies, with recycling programs emerging as an independent initiative financed by municipalities, mostly in urban areas. On the other hand, the municipal budget tends to be linked to the wealth of their inhabitants. Consequently, an efficient municipal resources allocation policy to support recycling programs is especially crucial for the most vulnerable population, often located in rural areas. In this paper, we address the problem of optimal allocation of resources for the adoption of a recycling program by municipalities located in both urban and rural areas of a developing country, determining the best combination between two options: increasing and redistributing existing resources. Our research methods involve comprehensive data collection and mathematical modelling, adopting a logistic regression model proposed in the literature, formulating a non-linear optimisation model, and implementing a resolution method. In addition, recycling policies with equivalent results are described and analysed, discussing their political feasibility and economic efficiency. To illustrate our proposal, the case of Chilean municipalities is considered. Chile is a country from the Global South that belongs to the OECD and can be therefore compared to other documented cases. Although no official national data is available, we were able to collect figures by requesting information from every municipality in the country. The obtained results show an important lack of resources at the national level in MSWM, especially affecting rural areas. In this context, equivalent recycling policies with combined options could better favour rural municipalities. However, the average probability for the adoption of a recycling program by municipalities, although shows slight increases, is not enough for a substantial change towards a more sustainable waste management model. Our results illustrate the gap between urban and rural municipalities, the need to inject important funds into the system as a whole, and open the question of whether a more direct 'command and control' policy is required instead of just trusting the individual initiative of each municipality, even if more resources are provided. [ABSTRACT FROM AUTHOR]

In this paper, a multi-objective, multi-period, and stochastic mathematical model is developed to identify drought-resilient strategies for balancing human and environmental water needs given uncertainty about future water availability. The model makes sustainable water withdrawal/distribution decisions for the interconnected water reservoirs of a river network through balancing societal and environmental water needs. These decisions are restricted by the storage capacities of reservoirs and fluctuations of water availability over the planning horizon. The model relies on interval estimation of stochastic hydrological factors, which may be drawn from historical data or future climate projections. The model finds a compromise between drought resilience and satisfaction of water needs through a reliability level that represents the risk attitude of water decision-makers. Finally, the model is extended to include water conservation options. The extended model determines the spatial and temporal prioritization of water reservoirs for water conservation. The proposed models are tested on the Red River of the south-central United States. We quantify tradeoffs between human and environmental water needs and identify water sustainability strategies that are resilient to stochastic drought events. Our model is applicable to drought-prone river basins around the world where water managers seek to balance environmental and human water needs while remaining resilient to unexpected fluctuations in water availability. • Water withdrawal/allocation decisions are made for drought-prone river networks. • Trade-offs between societal and ecological water satisfaction ratios are analysed. • The proposed approach is resilient against hydrological uncertainties. • Spatiotemporal prioritization of water reservoirs for conservation is determined. [ABSTRACT FROM AUTHOR]