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Increasing energy prices and market volatilities force energy intensive industries to implement energy management systems in order to ensure competitiveness. In this paper, we focus on the strategic level of energy management, specifically, on the analysis of the internal and external conditions that form the basis for strategic development. For this, we selected the case of the Austrian paper and pulp industry. We applied a hybrid method by combining an analysis of strengths, weaknesses, opportunities and threats with an analytic hierarchy process which was based on a survey of expert opinion. The results show that cost-related factors predominate. According to our analysis, the four most important factors are all directly linked to energy costs, energy efficiency, and the energy market. Experts pay little attention to environmental issues or to energy market volatilities. Apart from that, the combination of an analysis of strengths, weaknesses, opportunities and threats with an analytic hierarchy process promises to be a valuable tool for strategic energy management. This is especially true for energy intensive companies and/or sectors, since it enables decision makers to take strategic decisions based on a systematic understanding of the main issues. [ABSTRACT FROM AUTHOR]

In order to synthetically evaluate the tribological properties of friction materials, fuzzy comprehensive evaluation model was developed. The analytic hierarchy process was introduced into the model to establish weight function. The paper-based friction materials with different CNTs content were chosen as the six projects. It is found that the comprehensive evaluation indexes are increased by 126–307% for the samples with 4–15 wt% of CNTs compared with the sample without CNTs. The judgment matrix has high consistency by consistency checking. And the evaluation results are also in accordance with the results obtained through the friction torque, surface structure and temperature. [ABSTRACT FROM AUTHOR]

Green hydrogen can be the transitional solution required to reduce anthropogenic emissions and enhance energy independency from fossil fuel. To improve green hydrogen adoption, a cluster-based infrastructure, called a hydrogen hub, is devised taking into account the demand-supply interplay coupled with transport ease. In this paper, we have identified sites across states that are conducive for hydrogen hubs. It involves a multicriteria decision-making (MCDM) framework deployed to assign priorities within competing set of criteria. A comprehensive analytical hierarchy process (AHP) is used to rank criteria that are connected to establish a functioning hydrogen hub. These criteria include, but not limited to, proximity to refineries, fertilizer plants, substations, chlor-alkali units, steel manufacturing plants, water availability, access to gas pipelines, railway line access, and finally distance to highways. Our analyses indicate that proximity to refineries and fertilizers scored higher (scores directly proportional to importance) while railway line access scored the least. These prioritised scores are used to spatially locate sites using geographical information system. In a total of thirteen states identified, Gujarat had the largest parcel of most suitable land for setting up hydrogen hub followed by Maharashtra and Andhra Pradesh. For India to set up a functioning hydrogen economy and achieve green hydrogen goals, it is important to identify states that can drive the agenda forward. This paper illustrates a way (amongst many available ways) to identify states based on their strength and capability to fulfil the national goal of 5 million tons of green hydrogen by 2030. • The paper addresses setting up of green hydrogen hubs in India based on a multi-criteria site selection framework. • Nine selection criteria covering aspects of hydrogen ecosystem proposed to identify site(s) suitable for hydrogen hubs. • Integration of AHP and GIS is used to ascertain land parcels where hydrogen economy can sustain across states in India. • Zones in 13 states were identified as potential hydrogen hubs. [ABSTRACT FROM AUTHOR]

Machine Learning as a Service, MLaaS refers to cloud-based platforms that provide machine learning tools and infrastructure to users, allowing them to access and utilize machine learning capabilities without managing the underlying hardware and software. Cloud service providers offer scalable and flexible resources, enabling businesses to train and deploy machine learning models efficiently and cost-effectively. Multi-Criteria Decision making, MCDM helps individuals or organizations make choices when multiple criteria or objectives are involved. It aims to find the best alternative among a set of available options by considering various criteria or factors that are relevant to the decision. Machine learning as a service (MLaaS) and MCDM are two distinct concepts that can be combined to create powerful decision-making solutions. The present paper proposed an integrated approach based on the Analytic Hierarchy Process and TOPSIS method for choosing the best MLaaS cloud. Four alternatives for MLaaS cloud were analyzed based on seventeen shortlisted criteria. Based on the calculations, conclusions have been reached and potential study areas have been identified. [ABSTRACT FROM AUTHOR]

CO 2 sequestration is an effective technology for reducing greenhouse gas effect. To ensure the safety, assessment of well applicability should be conducted before CO 2 sequestration. However, current studies mainly focus on identifying which barrier has the highest risk of leakage rather than selecting a target well for injection in specific geological formation. To further investigate, this paper proposes well applicability assessment method combining reservoir and wellbore properties together for CO 2 sequestration. A novel assessment system combing Fuzzy comprehensive evaluation and Analytic hierarchy process has been established. Twenty-nine indexes subjected to seven categories (i.e., formation, well, cement sheath, cementing quality, casing, tubing, and wellhead properties) are taken into consideration. The weighting factors of these seven categories are 0.0673, 0.0552, 0.096, 0.1537, 0.2283, 0.2637 and 0.1369, respectively. Tubing and casing properties have the greatest influence on safety injection. Furthermore, the proposed system has been applied to S gas reservoir, China. Results show that Wells #P1 and #P2 are suitable for injection. Since more comprehensive indicators are considered comparing with previous studies, the results are more accuracy and objective. The findings of this paper could help efficiently and effectively evaluating well applicability for CO 2 sequestration and reducing the risk of CO 2 leakage. [ABSTRACT FROM AUTHOR]

Geospatial techniques are useful to understand the groundwater resources assessment, development, and management. Groundwater mapping is essential to counter the excessive withdrawal of groundwater and fulfil the need of drinking, irrigation water in hard rock areas. Currently, the main problem is facing the groundwater level is decreasing due to less rainfall, climate changes and increasing demand, which is under in the hot zones. This results can be more useful for future challenges, sustainable development and demand to Jakham river basin. The main objective of this paper to demarcated the groundwater potential zones (GWPZ) using geospatial techniques for the hard rock region with the reference of aquifer parameters. In this paper, we have used to total eight thematic layers such as geomorphology, land use, soil, topographic elevation, slope, post-monsoon groundwater level (GWL), net recharge, and transmissivity, which are prepared from satellite data and field verification. All thematic layers were integrated for assigning the weights to demarcation of the groundwater potential zones in the RS and GIS environment. The selected thematic layers and features were assigned weightage and normalized by the analytic hierarchy process (AHP) technique. Finally, the thematic layers were systematically integrated using weighted overlay analysis within a GIS environment. We have classified into five GWPZ classes i.e. very high, high, moderate, low, and very low for basin area using GIS, and AHP methods. The study area result indicated that high and moderate zone, which is confined in the central part of the basin, covers 2.43 % and 43.88 % area, respectively. The low (49.21 %) and very low (4.25%) GW potential zone is under the confined aquifer in the high slope and rock outcrops formations near the basin boundary. The final GWPZ map was validated with groundwater level fluctuation data, which illustrates the accuracy of the adopted approach. This unique approach and conclusions of this work may also help to develop the framework and policies for swiftly analyzing groundwater recharge planning, development and locating the artificial recharge structures in the other semi-arid, arid and hard rock regions. [ABSTRACT FROM AUTHOR]

• A new simulation methodology, intended bounded rationality methodology, is proposed. • Evaluation cost-benefit of different aspects of decision support techniques. • Classification of errors that a decision support technique can generate is proposed. • Consistent erroneous judgments and inconsistent correct judgments are possible. • A case where consistency condition in AHP provides maximum 5% of the expected return. Expert's judgments have been crucial in the development of decision theory; however, what criterion to use in the selection of experts remains an issue to address. Decision support techniques proposed to improve the quality of expert judgment decision making consider a demonstrated inconsistency of the judgments expressed by an expert as a criterion of exclusion in the decision-making process of such expert. Although consistency appears to be a desirable condition to qualify as "expert", little is known about the quality of the decisions made imposing consistency as the expert qualifying condition. This paper proposes a simulation methodology, based on an automaton programmed to make decisions in an intended but bounded rational way, to assess the cost-benefit of different aspects of decision support techniques. Within this methodology, the imposition of the consistency condition in the selection of experts is studied. In particular, the paper shows with a case study example that the Analytical hierarchy process (AHP) decision support technique expected payoff is at most 5% higher when implementing Saaty's consistency criterion of the expert's judgments than when the consistency criterion is not considered. [ABSTRACT FROM AUTHOR]

This paper presents a variation of the classical Diet Problem, in which a Linear Programming model is applied in order to minimize meal costs while meeting the nutritional needs of the individual. With a hybrid application of the method Analytic Hierarchy Process (AHP) – by using the software Three Decision Methods (3DM) – and a Linear Programming (LP) model, the objective of this work was to ensure that 4 previously defined meals were chosen, out of a total of 7, to be part of the menu of a Brazilian company that provides lunch to its employees. With the AHP Method it was possible to determine the preference of employees for each meal, according to a series of criteria, and define a ranking with scores for each one of them. Using these scores, a Linear Programming model was created whose objective-function was to maximize employee satisfaction with the selected meals, while meeting the maximum cost constraint assigned to this selection. The PL model returned a satisfactory result, in which, counterintuitively, not the 4 meals with the highest score in the application of the AHP method – to maximize satisfaction – nor the 4 cheapest meals – to respect the cost limit – were selected, but a combination of these two characteristics. The methodology proposed in this paper can be applied for the most diverse problems of the public, private or military sectors. [ABSTRACT FROM AUTHOR]

With the evolution of Industry 4.0, the most advanced technologies have been invented and due to rapid globalisation, supply chains (SC) have become vulnerable to various risks. Risk management performs a key role in operating SC effectively in variety of uncertain circumstances. This paper aims to reveal the adaptability of digital technologies in supply chain networks, identify and analyse the various emerging supply chain risks in the industry 4.0 environment, and develop a framework to mitigate the risk level. A systematic literature review was conducted to identify and analyse the emerging supply chain risks, and Analytical Hierarchy Process (AHP) method was used to develop a conceptual risk mitigation framework. The contribution of this study lies in the taxonomy study, and findings revealed that digitalisation of supply chain design for risk mitigation shed light on future research. Additionally, it focuses on the potential to enhance supply networks' efficiency and responsiveness. [ABSTRACT FROM AUTHOR]

Decision analysis is a key aspect in improving slums intervention strategies utilizing a variety of tools to evaluate all relevant information that support decision-making process for dealing with the complexity of slums interventions policies. This paper presents a framework integrating Multi Criterion Decision Analysis (MCDA) with (GIS) based decision support tool to quantitatively assess land suitability for site relocation of an urban slum site utilizing Analytical Hierarchy Process (AHP), which is commonly used for fastest growing decision-analytic techniques in several disciplines for the determination of various aspects weights. Herein Batn Al Baqara region (which is located in south of Cairo) was selected as study area to be relocated as it was considered among the most difficult to deal with, three proposed relocation sites were selected and analyzed using MCDA-GIS Model. Twelve different criteria were utilized to evaluate the degree of suitability of the relocation sites. A five degree of suitability were employed according to the different criteria scores for each site. The results supported that Al Asmarat is the most suitable site for the relocation of slum since it achieved the highest evaluation score (84.92 %) when the model was applied to the relocation sites. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid fuzzy AHP (Analytic Hierarchy Process) – DEMATEL (Decision Making Trial and Evaluation Laboratory) approach to determine the most relevant criteria to measure the performance of municipal Emergency Medical Service (EMS) providers transparently and comprehensively. Allocation of emergency medical services affects public finances and the district's social management. Therefore, evaluating EMS providers' performance is crucial based on multiple factors, such as equipment, vehicle condition, pre-hospital care, diagnoses, costs, staff training, and financial stability. Multi-criteria decision-making tools can help to obtain a comprehensive and objective assessment of EMS providers' performance rather than relying solely on response time, which can be subject to random fluctuations. The proposed approach uses a hybrid fuzzy AHP-DEMATEL that determines that the managerial criteria are more relevant in the process, weighing 47.4%. This model will help ensure the quality and transparency of emergency medical services and guarantee that resource allocation is accountable. This will solve the district's current challenge when deciding whom to assign the EMS concessions. The results of this study demonstrate the significance of using a comprehensive evaluation model to ensure the quality of emergency medical services and enhance the decision-making process of state authorities. [ABSTRACT FROM AUTHOR]

There are different studies has introduced different methods and techniques to improve the performance and to reduce the delays in delivering construction projects. The selection of qualified contractors has a crucial importance which ensures delivering projects within the required time, quality, and cost. There are different national classification systems for contractors which are based on some similar and different criteria. This paper aims to develop a new model that helps in evaluating contractors in pre-tendering stage. The establishment of this model starts by listing 39 different criteria that are extracted from previous related studies. Then, 9 experts conducted a pairwise comparisons of those criteria using Analytical Hierarchy Process (AHP) which resulted in 10 important criteria that should be used in evaluating construction contractors in pre-tendering stage. Those 10 criteria were then evaluated by 21 specialized mangers in different contract departments to get the weight of each criterion using Multi Attribute Utility Theory (MAUT) which converts those different criteria that have different attributes dimensions to one unified measurement scale identified as the multi-attribute "utility". At the end, the selection criteria are evaluated using numerical and nominal scale to calculate the final score using the weights of those criteria which will allocate the contractors that can go to the tendering stage. As this model introduces a method for evaluating contractors before tendering stage, it also allows the clients or owners redefine the selection criteria and to decide the minimum result to allow contractors to move to the tendering stage. So, this model will help decision makers to ensure that the contractor's characteristics and capabilities meet the requirements of the allocated project. Effective and objective qualification processes will serve both parties, owners, and contractors, in delivering construction projects. The criteria of this model are established based on the requirements of the construction industry in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Traffic risk hinders the development of human society. Due to the influence of weather and climate, the traffic risks vary in different time periods. This paper innovatively reconstructs the criterion system for evaluating regional traffic safety risk from a time series perspective. On the basis of the novel criterion system, this paper proposes a monthly dimension regional public traffic safety risk grading model with Analytic Hierarchy Process Sort II (AHPSort II) and Criteria Importance Though Intercriteria Correlation (CRITIC) (i.e., AHPSort II-CRITIC method), in which, AHPSort II is used to obtain the traffic safety risk levels of different regions, and the CRITIC is used to determine the weight vector of the criteria system. The proposed method is applied to evaluate the regional traffic safety risk levels of 31 provinces, municipalities, and autonomous regions in the Chinese mainland and some cities in Hubei province in the whole year of 2019. The results of this paper show that the traffic safety risk levels are high in June, July, and August, and the performances of other months are relatively more optimistic. Finally, this paper puts forward some transport policy implications, which provide a suitable basis for policy formulation to reduce regional traffic safety risk. • A monthly dimension evaluation model for traffic safety risk is established. • An AHPSort II- CRITIC method is proposed to grade the risk levels. • Effectiveness of the method is verified by empirical analysis of cases. • A time perspective broadens the direction of regional traffic risk research. [ABSTRACT FROM AUTHOR]

In the face of increasingly agile product development, new challenges arise for assembly planning due to growing complexity. Within this paper, we show that the complexity-dependent combination of agile methods and traditionally plan-driven assembly planning procedures holds great potential for mastering planning complexity. Thus, a methodology towards hybrid assembly planning is elucidated with a focus on selecting dominant planning methods for specific planning scopes within this paper. Based on a detailed model of assembly planning as a system, the complexity requirements of different planning modules are determined. Therefore, an integrative complexity measure is developed to quantitatively operationalise complexity in a quasistatic-structural and a dynamic-functional complexity dimension. In order to identify dominant planning methods, the complexity potentials of agile and plan-driven methods are examined in an Analytic Hierarchy Process expert study with 22 participants. Within a decision model, dominant planning methods are selected for specific planning modules by matching the quantified complexity requirements with the complexity potentials of agile and plan-driven methods. Based on the systematic method selection, dominant planning methods for specific planning scopes can be tailored into a project-specific hybrid process framework. The approach to hybrid assembly planning enables optimised planning results through the improved mastery of complexity. [ABSTRACT FROM AUTHOR]

The research uniquely focuses on advancing the field of fuzzy sets, specifically proposing a novel approach using Hexagonal Type-2 Fuzzy Variable (HT2FV), to handle higher degrees of uncertainty. Flooding, a recurrent and impactful phenomenon, necessitates a robust approach to effective disaster management. The study delves into the humanitarian supply chain dynamics during movement crises and flood catastrophes, introducing a novel methodology to harness the potential of HT2FV. Central to the paper is the innovative defuzzification concept of Critical Value (CV) reduction, strategically employed to eliminate fuzzy components within HT2FV, transforming it into crisp data. The research extends its novelty by proposing a comprehensive approach to distributing relief materials, employing a Multi-objective, Multi-level, Multi-modal (MOMLMM) approach, with a primary focus on boats for inundated areas. Significantly, the study aims to optimize the allocation of resources, minimize time and cost under uncertain environments, and enhance disaster relief operations. The paper is the first to use new hexagonal fuzzy numbers (HFNs) and focuses on how they can be used to sort vulnerable areas using the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods of the Multi-Criteria Decision-Making (MCDM) process. A case study of the 2022 Assam flood is looked at and solved using the Weighted Sum (WS), Neutrosophic Compromise (NC), and Goal Programming (GP) systematically on the LINGO solver to see if the suggested method can be used. Further, sensitivity analysis is employed to establish optimal credibility levels to validate the proposed methods. A real-life case study lends practicality, substantiating the approach's efficacy. At the same time, comprehensive comparative analysis compares and contrasts findings from different studies to synthesize existing knowledge and identify future scope, contributing significantly to the field of fuzzy sets. [ABSTRACT FROM AUTHOR]

This paper considers the problem of selecting a state-made electronic document management system (EDMS) using the analytic hierarchy process (AHP) model. The problem of EDMS selection from two available variants is analysed and the selection criteria related are highlighted on the basis of the literature and the authors' experience. Calculations related to pairwise comparisons and prioritisation between criteria and variants form the core of the paper. This problem is only applicable to municipalities in Poland that have implemented an older state-made system; based on pair-wise comparisons, retaining the older system is preferable to implementing the new state-made EDMS because of the lack of integration of the new EDMS with internal systems. [ABSTRACT FROM AUTHOR]

Hadoop is an open-source framework that is widely used to store and process large amounts of data. Its core component is called YARN that is responsible for resource management and job scheduling for Big Data applications. Although YARN has very advanced processing performance. It suffers from resource allocation problems when used in a heterogeneous cluster serving multiple users. To deal with this heterogeneity and overcome the degradation of cluster, load balancing has become a major challenge for Hadoop run-time management. In this paper, an efficient resource allocation strategy combining multi-criteria decision-making and accurate clustering of nodes in a heterogeneous Hadoop environment is proposed. A multi-criteria decision approach relying on a modified analytical hierarchy process method is applied to assign a score to jobs depending on the resources requirements at run time. First, the proposed system profiles the available nodes by grouping them into clusters with similar performance. Second, the system performs a dynamic multi-criteria selection on resource requests by assigning scores to jobs according to their resource usage. Third, node groups and job scores are used to dynamically allocate jobs to the most appropriate resources in real time while keeping load balance in the heterogeneous cluster. The aims of this present paper are to optimize the resource utilization and achieve a high performance of the Yarn resource management by considering a heterogeneous environment. The experimental results demonstrate that the proposed algorithm provides the best utilization of available resources by 45% and 12% compared to fair and H-fair respectively, which implies a minimum job execution time in a heterogeneous cluster. [ABSTRACT FROM AUTHOR]

• To prevent depoliticization, urban resilience necessitates a social viewpoint. • Institutional power offer a guiding point of view for approaching the concept. • Framework for analyzing resilience's political orientation is innovation of paper. The concept of urban resilience, originating from ecological sciences, poses challenges in its introduction and explanation as an objective and approach in urban planning. Expanding the social and normative dimensions of urban resilience is challenging due to its conservative and non-political ecological background. Critically, the reductionist approach and depoliticization of urban resilience in planning are significant concerns. This paper addresses the analysis of institutional power orientations in defining the concept of urban resilience and targeting its achievement. According to this purpose, this paper provides a theoretical framework for analyzing institutional power orientations towards earthquake resilience, developed in two primary parts, as the main novelty and contribution of the proposed research. The city of Karaj is selected as a case study to test this framework. The research methodology involves a triple analysis of epistemology, ontology, and axiology of resilience from institutional power point of view, utilizing qualitative content analysis, semi-structured interviews, and the Analytic Hierarchy Process (AHP) questionnaire. In conclusion, emphasizing the importance of exploring the logical connection between ideas, the need for attention, and analyzing decision-taking processes is highlighted based on the research findings. [ABSTRACT FROM AUTHOR]

The full utilization of solar energy resources along the road is an effective method to solve the energy shortage in transportation. The key to this is an accurate evaluation of solar energy resources, which provides the rationale for the optimal location of road photovoltaic (PV) projects. However, determining the availability of solar energy resources in road areas before route corridor planning remains difficult. To address the issue, this paper developed a standardized method. Firstly, this paper analyzed the critical factors affecting the availability of solar energy resources. They were meteorology, topography, land use type, geology, and location. On that basis, we developed a four-level evaluation indicator system. Then, it proposed a multi-indicator evaluation method based on the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). It used AHP to calculate the weights of each indicator, with solar radiation being the most important. It used GIS to analyze and overlay the spatial distribution of multiple indicators to obtain the map of suitability grades, which could be used to route corridor selection for road PV projects. It also used a case study to demonstrate how the method is applied. The findings show that the method can accurately evaluate the availability of solar energy resources. Furthermore, it studied the appropriate division of evaluation units and it is advised that they shouldn't be larger than 30 m × 30 m. These results provide guidance as a reference for the application of road PV projects and site selection for route corridors worldwide. That will promote the integration of transportation and energy in the future. • The paper addresses the problem of solar energy resources evaluation in road areas. • The paper establishes a universal evaluation indicator system. • The paper proposes a standardized evaluation method based on AHP and GIS. • This method presents the obtained evaluation results as suitability grade map. • This method helps select route corridors with good power generation potential. [ABSTRACT FROM AUTHOR]

The supercritical carbon dioxide (S–CO 2) Brayton cycle is a potential technology for recovering waste heat from compressed natural gas (CNG) engines. To choose suitable cycle configurations is important considering the complex operating characteristics of CNG engines. The traditional evaluation models of the S–CO 2 cycles configuration are relatively one-sided without the comprehensive considerations of evaluation metrics. On the basis of the analytic hierarchy process and information entropy theory, this paper proposes a multi-dimensional comprehensive evaluation method for S–CO 2 cycles from three perspectives: thermodynamic, economic, and environmental performance. A thermoeconomic performance optimization is conducted using a non-dominated genetic algorithm Ⅱ. Unlike most of the existing researches that use a single stable operating condition, this paper considers the full operating conditions of engines. Results show that the recompression cycle has the best overall performance among the investigated cycles with an exergy efficiency and electricity production cost of 67.20 % and 0.45 $/kWh, respectively. The efficiency improvement of the CNG engine coupled with the WHR system can reach up to 6.31 %. This study can provide a new reference for the comprehensive multidimensional evaluation and performance characteristics and optimal performance acquisition under full engine operating conditions of the S–CO 2 cycle. • A multi-dimensional comprehensive evaluation method for S–CO 2 Brayton cycle. • Thermo-economic optimization under full operating conditions is conducted. • The optimal operating regions of decision variables are obtained. • The CNG engine efficiency with waste heat recovery can be improved by 6.31 %. [ABSTRACT FROM AUTHOR]

This paper presents findings of strategies for the resilience of natural structures in biological systems with applications in manufacturing. Natural structures are fundamental to the design, manufacturing, and resilience of biological systems, and system of systems. This paper presents the main ten key strategies by which natural structures achieve resilience and their relevance to manufacturing, discussed through representative examples. These ten strategies are selection and organization of sizes and shapes, the hierarchy of branching, multifunctional surfaces, distribution of division of roles (labor), distributed structures and systems, functional redundancy, scale and management of defects, self-healing and reorganization, sensory networks, and aesthetics. [ABSTRACT FROM AUTHOR]

In every decision-making problem which involves two or more criteria, there is to identify the relative importance of those criteria in order to make a proper decision. Very often, a decision-makers employee, for this purpose, subjective weighting methods, such as Analytic Hierarchy Process (AHP) or Ranking Comparison (RANCOM). However, there is no simple way to compare the quality of the weights identification using different methods. To address this issue, this paper proposes a simple but Efficient Weights Similarity Coefficient, which allows us to evaluate the relative performance of different subjective weighting methods. Furthermore, we propose a framework that utilizes the proposed coefficient in order to provide more complete comparison results. To demonstrate the applicability and effectiveness of the proposed framework, a case study is performed to compare two popular weighting methods: AHP and RANCOM. The results of the comparison prove that proposed coefficient with the combination of the proposed framework is an Efficient instrument for weighing methods comparison. [ABSTRACT FROM AUTHOR]

In this paper, novel multi-objective microgrids (MGs) formation method-based darts game theory optimization algorithm is proposed. The main objectives are to minimize the total losses, amount of load-shedding, and total restoration cost while ensuring a variety of topological and electrical constraints. The network graph theory represents the formed MG, and the non-linear equations of power flow and loss calculations are adopted in the MG formation model. In the proposed model, the DRERs include diesel generators, fuel cells, micro-turbines, and renewables wind and PV units with energy storage systems. The demand response program includes curtailable loads to improve load profile reduction during peaks. To assess the system's resiliency under extremely inevitable incidents, resiliency metrics are applied. To validate the effectiveness of the proposed approach, the modified IEEE 33-bus test system is utilized. Single-fault and multiple faults disaster case studies are performed with and without considering the emergency demand response program (EDRP). The results show the effect of EDRP in minimizing system losses, load-shedding, restoration cost, and improving the resiliency metrics after natural disasters. Finally, the analytic hierarchy process (AHP) model indicates the most efficient operation scenario while achieving the system objectives considering the problem alternatives. [ABSTRACT FROM AUTHOR]

• AHP-based method to eliminate redundant capacitance of ECT is proposed. • The causes of the generation of redundant capacitance is illustrated. • The method exhibits generality and possesses engineering practical potential. To reduce imaging errors in electrical capacitance tomography (ECT) arising from redundant capacitance, this paper proposes a method to eliminate such redundancy, leveraging the analytic hierarchy process (AHP). Firstly, an analysis is conducted to elucidate the origins of redundant capacitance, which are attributed to the polarization effect. Secondly, the paper presents a comprehensive outline of the algorithmic structure underpinning the proposed method for redundant capacitance elimination. Finally, the universality and anti-interference capability of the method are verified through simulations and practical experiments across various scenarios: encompassing typical medium distributions, diverse image reconstruction algorithms, and various sensor structures. The results conclusively demonstrate that the proposed method exhibits superior image reconstruction effect in comparison to traditional redundant elimination methods. [ABSTRACT FROM AUTHOR]

• A new decision-support model for sustainability assessment of urban regeneration. • The indicator-based model integrates social, economic, environmental and governance aspects. • Social aspects contributed the most to the overall sustainability weighting across the four dimensions. • Building and land use were found to be the most important of the 17 evaluation categories. This paper presents a comprehensive evaluation model comprising indicators spanning four dimensions: social, economic, environmental, and governance. Extensive indicators were gathered from the literature and subsequently subjected to a rigorous screening, validation, and finalization process by a panel of 25 international experts through a Delphi survey. The relative weights assigned to each indicator were determined utilizing the Analytic Hierarchy Process (AHP). The findings reveal that the social dimension carries the greatest significance in achieving sustainable urban renewal (SUR), closely followed by the environmental dimension. In terms of assessment categories, the highest priority and weight (0.1186) were attributed to "building and land use," while "economic viability" (weight=0.1049), "policymaking" (weight=0.0982), "community involvement" (weight=0.0882), and "housing provision" (weight=0.850) were also identified as significant areas. The paper emphasizes that these proposed indicators can serve as valuable tools to inform the review and enhancement of urban planning guidelines and policies at the local, state, and national levels, fostering sustainable urban regeneration. [ABSTRACT FROM AUTHOR]

In pharmaceutical warehousing operations, a scientific and reasonable medicine and shelf matching strategy can improve medicine shelving efficiency and manual work efficiency. However, the traditional matching strategy has the problems of static matching and low matching efficiency, so this paper proposes the matching algorithm for drugs and shelves based on the fuzzy analytic hierarchy process and Bayesian convolutional neural network (FAHP-BCNN). First, we propose a drug-shelf matching degree model and discuss the influence of the dynamic matching process on the matching results by studying two parts: the attribute matching degree and the dynamic matching influence degree. Secondly, this paper quantitatively assessed the importance of the two matches by means of the fuzzy analytic hierarchy process. Finally, we mapped the massive matching information onto Bayesian convolutional neural network nodes, constructed a dynamic matching network model, and obtained competitive matching strategies and results. The experimental results show that the FAHP-BCNN algorithm exhibits better matching results in all three scenarios with different quantity ratios of drugs and shelf matching. Compared with the fixed cargo matching strategy of the ABC classification method, the FAHP-BCNN algorithm shows excellent performance in both the manual walking distance index and fatigue index. In summary, the drug-shelf matching algorithm based on FAHP-BCNN is effective and can provide theoretical support for pharmaceutical warehousing enterprises to perform drug-shelf matching. [ABSTRACT FROM AUTHOR]

This paper presents a novel game allocation method for solving the task allocation problem in underwater multi-AUV dynamic confrontations. The proposed method addresses incomplete information using a multi-objective evaluation model and interval ranking. An improved particle swarm optimization (PSO) algorithm, incorporating a hybrid strategy, is introduced to determine the Nash equilibrium of the game model. Firstly, the paper introduces the problem of underwater multi-AUV confrontations and establishes a game model based on interval numbers. Secondly, it develops a multi-target interval evaluation model considering survival value, strike income, and ammunition consumption. Combined with the analytic hierarchy process (AHP), each objective in the evaluation model is weighted to adapt to the battlefield situation with changing confrontation tasks and decision preferences. TOPSIS, relative entropy, and probability degree sort the interval income for optimization. Finally, an improved PSO algorithm called GSPSO, combining the good point set theory (G) and speed control factor (S), solves the optimal allocation problem. Simulation results demonstrate that the probability degree-based ranking method achieves higher resolution incomes, aiding precise optimization. The algorithm improves convergence speed, accuracy, and global optimization ability by increasing population diversity and iterative effectiveness, ensuring real-time decision-making in complex game scenarios. • A multi-objective evaluation model is designed using the analytic hierarchy process. • Interval ranking and optimization contributes to precise decision-making. • Enhanced particle swarm optimization with good point set and speed control factor. [ABSTRACT FROM AUTHOR]

Several methods of preference modeling, ranking, voting and multi-criteria decision-making include pairwise comparisons. It is usually simpler to compare two objects at a time, furthermore, some relations (e.g., the outcome of sports matches) are naturally known for pairs. This paper investigates and compares pairwise comparison models and the stochastic Bradley–Terry model. It is proved that they provide the same priority vectors for consistent (complete or incomplete) comparisons. For incomplete comparisons, all filling in levels are considered. Recent results identified the optimal subsets and sequences of multiplicative/additive/reciprocal pairwise comparisons for small sizes of items (up to n = 6). Simulations of this paper show that the same subsets and sequences are optimal in the case of the Bradley–Terry and the Thurstone models as well. This somehow surprising coincidence suggests the existence of a more general result. Further models of information and preference theory are subject to future investigation to identify optimal subsets of input data. • Multiplicative/additive/reciprocal pairwise comparisons vs. Bradley–Terry model. • Their equivalence is shown in case of consistency. • All filling in levels are investigated. • The same subsets of comparisons are shown to be optimal even in inconsistent cases. • Results raise new research direction: Are such coincidences valid in further models? [ABSTRACT FROM AUTHOR]

The proportion of middle-aged and aging workers is increasing year by year in the construction industry. Affected by their physical functions and other conditions, the death rate of aging construction workers is higher than that of the workers in other age groups, which brings higher risks to the safety of the industry. Therefore, the paper aims to determine the main risk factor of safety brought on by the aging construction workers, and the degree of influence of safety risk factor on aging construction workers. Through the design of the questionnaire, the number and type of index to be studied are selected. The 6 first-level indexes and 30 second-level indexes were selected from 100 indexes. The AHP method was used to evaluate the influence of aging construction workers on the safety risk factor. The classification of work contents of aging construction workers in different age groups is proposed to reduce safety risks and provide an effective basis for management. The significance of this study is as follows: (1) The concrete analysis of index affecting the safety risk of aging construction workers has enriched the existing academic research; (2) the quantitative risk index system in the study, provides a reference value for further research in the academic circle; (3) The study of this paper has certain reference significance for construction companies and government regulatory departments to formulate policies and measures, such as job classification of aging workers in different ages and restrictive conditions for high-risk work. [ABSTRACT FROM AUTHOR]

Climate change and scarcity of energy sources have put developing countries in a situation that demands emergency future planning for matured renewable technologies in order to continue sustainable progress and provide clean and cheap energy to masses. This paper provides a comprehensive structure of site suitability for utility scale solar PV and wind energy projects considering criteria critical to each technology while only using criteria with absolute necessity for varying scenarios incorporating Multi Criteria Decision Analysis (MCDA) along with Geographic Information System (GIS). A novel approach is also considered for far-off areas potentially deprived of electricity access for small scale solar PV implementation. A total of eight sub-criteria were considered in site selection process regarding wind and solar energy, analyzed using Analytical Hierarchy Process (AHP) in order to rank criteria depending on their importance to selection process. Resulting methodology was applied to case study of Pakistan, a developing country with growing climate change emergency and ongoing power crisis. End results showed 25.28% area suitable for utility scale solar PV farms, 5.93% area suitable for utility scale wind farms and 40.02% suitable area for small scale solar PV farms. [ABSTRACT FROM AUTHOR]

The whole process to an accident contains three components including power, origin, and intermediate. Existing accident models always fail to explore the process well. In this paper, a system is considered to be powered by the nature of spontaneous disorder determined by Entropy Increase Principle. The origin is identified as social factors through reviewing the literature regarding hierarchical levels of accident causes. Intermediate is elaborated within the framework of Darwin's Natural Selection. In intermediate, each type of unsafe factors have to struggle with both other unsafe factors and 10 types of safe factors. The unsafe factors which fail to be controlled before an accident occurs must have at least one of variations including latency, mildness, and tendency when they evolve every time. Finally, based on a case study, a comparison is made with Fuzzy Analytic Hierarchy Process. The results from that demonstrates the advantages of the proposed accident model. [Display omitted] [ABSTRACT FROM AUTHOR]

Customer feedback and satisfaction are critical indicators of success in the hospitality industry. The influence of customer reviews on the decisions of other customers to visit and on the brand reputation of hotels necessitates that hotel managers conduct a thorough analysis of customer satisfaction. This paper presents an approach for assessing the overall customer satisfaction of hotels by using the Analytic Hierarchy Process (AHP) method, the SERVPERF scale, and the 2-tuple linguistic model. The five dimensions of the SERVPERF scale have been customized to assess customer satisfaction in hotels, considering various hotel aspects such as rooms, service, cleanliness, and so on. The AHP method is applied to obtain the importance of the SERVPERF scale for each aspect of the hotels. The 2-tuple linguistic model is employed to address the issue of information loss in linguistic information fusion and enhance the comprehensibility of the results for hotel managers. The functionality of this proposal has been evaluated through a case study of luxury hotels in London, using 15,511 customer reviews gathered from TripAdvisor. The results show that the proposed model effectively captures and summarizes customer satisfaction with luxury hotels in London, allowing hotel managers to identify areas for improvement and discover potential business opportunities. This ultimately helps to increase customer satisfaction. [ABSTRACT FROM AUTHOR]

Emerging innovative manufacturing systems combine cyber-physical systems (CPS), the Internet of Things (IoT), and data analytics to develop a framework for predictive and adaptive purposes. The fifth industrial revolution, or Industry 5.0, envisions human-machine cooperation in a mutually beneficial symbiotic relationship. Human intelligence is responsible for high decision support providing feedback to the model, and the machine is dedicated to the empirical processing that builds the model. This paper presents a human-centric framework incorporating various maintenance stakeholders' perceptions to assess the relationship between key maintenance factors affecting manufacturing sustainability. The work methodology integrates two methods: the fuzzy analytic hierarchy process (F-AHP) and the elimination and choice expressing reality (ELECTRE III). The F-AHP is used to compute the relative weights of the evaluation criteria of the maintenance factors. Then, the criteria weights will be used as the input for the ELECTRE III method to rank the maintenance factors. It was observed that the proposed approach is robust and can classify the maintenance factors according to their importance to sustainable manufacturing. [ABSTRACT FROM AUTHOR]

Supply chain management is critical for any organization. To improve the performance of a firm's supply chain, it is important to have a freight forwarder evaluation process in place. This paper develops an analytical hierarchy process (AHP) methodology to perform a multi-criteria evaluation of freight forwarders. It analyzes different criteria that would be employed in the evaluation and selection of forwarders. The problem of choosing the best freight forwarder is evaluated in terms of quality of service, specialized service, network, competitive price, information and technology, and sustainability. A total of fourteen sub-criteria are considered including quality of service, network, information and technology, and sustainability. The study revealed that specialized service is the most important criterion with a weight of 54.3% followed by quality of service, competitive price, information and technology, network, and sustainability. Proven experience is the most important sub-criterion with overall weight of 36.2% followed by knowing the regulations with overall weight of 18.1%. Freight forwarder B is the best option with the highest weight with respect to proven experience and knows the regulations with values of 3.62 and 1.629, respectively. [ABSTRACT FROM AUTHOR]

Multi-criteria decision making (MCDM) methods have become increasingly popular in site selection decision-making of renewable energy power plants because they consider multiple conflicting goals and decision-maker preferences. In this paper, a systematic literature review of MCDM applications for renewable energy site selection is performed, covering a total of 85 papers published from 2001 to 2018 in high-level journals (chosen from the ScienceDirect database). This paper has summarized the exclusion criteria and evaluation criteria of site selection for five energy sources. The five site selection stages, criteria selection, data normalization, criteria weighting, alternative evaluation and result validation, are revealed by content analysis. All papers are further classified by the date, energy source, journal of publication, country of author affiliation, and study area. It is found that different energy sources emphasize different criteria; however, some similarities exist. Literature surveys and expert opinions are most common criteria selection method. Reclassification is most frequently used data normalization method. The analytic hierarchy process is popular for weighting. In alternative evaluation, geographic information systems and weighted linear combination are the most popular tools. Varying the criteria weights is most commonly used result validation method. • This is the first review of MCDM applications for renewable energy site selection. • It covers five energy sources: solar, onshore wind, offshore wind, wave and tidal. • It focuses on two types of criteria and methods in the five site selection stages. • It also involves methods for data normalization and result validation. • The combination of GISs and MCDM is the most popular tool in this research area. [ABSTRACT FROM AUTHOR]

The popularity of hydrogen refueling stations in China is hindered by unreasonable site selection and high initial costs. Built gas stations with large consumer groups and reasonable locations can be expanded into oil-hydrogen combined stations. which can effectively reduce construction costs and approval complexity, improve hydrogenation infrastructure and reduce hydrogenation costs. Taking Chinese social-economic environment into consideration, this paper created an optimal site selection decision framework for oil-hydrogen combined stations to achieve the goal of reducing construction costs, transportation costs and carbon emissions in the whole process. A two-stage criteria system including veto criteria system and evaluation criteria system was established, and fuzzy analytic hierarchy process (AHP) method and TOmada De decis ão Interativa Multicritério (TODIM) method were utilized to determine the criteria weight and obtain the ranking of alternatives respectively. Finally, a case study was conducted and the most suitable gas station site for the construction of oil-hydrogen combined station was determined. Moreover, the economics of the several hydrogen sources were discussed from the perspective of best site selected, it is concluded that hydrogen from natural gas or coal is still the best hydrogen source for oil-hydrogen combined stations. • A comprehensive site selection criteria system including veto indicators and evaluation criteria was established. • A fuzzy AHP-TODIM-based decision-making framework for site selection for oil-hydrogen combined stations is established. • The economics and carbon emission levels of different hydrogen sources chosen by oil-hydrogen combined station are discussed. [ABSTRACT FROM AUTHOR]

Stirring tanks are regarded as pivotal equipment for solid-liquid suspension operations in industrial processes such as adsorption and crystallisation, and its performance is complex in relation to the pulp phase, structure and process conditions. However, the traditional design method for stirring tank structure is sophisticated and time-consuming, which greatly limits the design efficiency. To address the high cost and inefficiency of traditional design methods, this paper performed a multi-objective optimal design of stirring tank based on numerical simulation, surrogate model, NSGA-II, Entropy Weighting Method and Analytic Hierarchical Process. Firstly, the flow field state of stirring tanks with different structural dimensions and operating parameters was simulated with computational fluid dynamics (CFD), which was subsequently validated by Particle Image Velocimetry. Then, for the key parameters including stirring speed, stirrer diameter, stirrer height from the bottom and paddle pitch, experiments were designed using the Latin Hypercube method to establish a Kriging model based on the gained simulation data. Afterwards, the Pareto front was obtained from the optimization using NSGA-II with two objectives of stirring power and suspension uniformity. The result of Analytic Hierarchy Process and Entropy Weighting Method showed that the selected optimal solution can improve the suspension uniformity by 0.7 % while reducing power consumption by 48.3 % compared to the initial design. [Display omitted] • An multi-objective optimization model for stirring tank was developed. • Combination of Kriging and NSGA-II reduces the consumption of resources dramatically. • Balancing objective and subjective factors by integrating AHP and EWM. • The optimal solution reduces energy cost by 48.3 % at no loss in. [ABSTRACT FROM AUTHOR]

• Reusing and re-functionalizing abandoned historical buildings is an urgent challenge. • An innovative AHP-based model for the Highest and Best Use of historical assets is proposed. • We define a new set of indicators in accordance with SDGs and the European Quality Principles. • The application of the proposed model has important policy implications and it can contribute to the preservation of historical heritage. Cultural heritage can play a strategic role in achieving the sustainable development goals, as widely recognized worldwide by the United Nations, UNESCO, ICOMOS, as well as by many regional and national institutions. It is needed to implement the principles stated in international and national recommendations in new approaches and tools, both to preserve the historical assets and revitalize them in a circular economy perspective. The paper discusses the challenges of assigning new uses to abandoned historic buildings that still retain values to be protected and passed on to the future. Specifically, the research proposes an innovative analysis model based on the algorithms of the Analytic Hierarchy Process (AHP) and the employment of evaluation indicators established in accordance with 2030 Sustainable Development Goals (SDGs) and European Quality Principles. The model is applied to the case study of Villa Venusio, an 18th century noble house built in Metropolitan Area of Naples (Italy), which is currently in an advanced state of decay and abandonment, awaiting architectural, functional, and technological restoration. This study demonstrates that the proposed model can be an essential decision support for the most effective use of historic buildings, by respecting any social, economic, and cultural value. This has important policy implications in the processes of allocating public funding for the rehabilitation of architectural heritage. [ABSTRACT FROM AUTHOR]

• Evaluated the suitable sites for implementing utility-scale Photovoltaic farms in Saudi Arabia. • Multiple technical and economic factors are incorporated. • Fuzzy AHP method is used to weight the criteria. • PROMEETHEE II method is used to evaluate the alternatives. Although Saudi Arabia can benefit from implementing photovoltaic (PV) solar power projects to generate power, there are some environmental, economic and technical challenges which can affect the efficiency and cost effectiveness of these facilities. The goal of this paper is to build a site suitability model to identify the suitable sites for implementing solar PV solar projects in Saudi Arabia. Fuzzy analytical hierarchy process (AHP), as a weighting technique, and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE II) method are combined to appropriately evaluate the suitable sites. 12 factors divided into two criteria (technical and economical) were incorporated to ensure minimization of construction costs while maximizing power output from the PV power plants. The resulting suitability map shows that Saudi Arabia has huge potential for implementing solar PV projects with approximately 376,623 km2 (65.1 %) of the total studied area considered, "most to highly suitable". In addition, a validation of the model's predictivity was conducted through an evaluation of the suitability map with respect to the future solar PV projects that Saudi Arabia is developing. The results showed that 90.6 % of the future projects fell within, "most and highly suitable" areas provided by PROMETHEE II suitability map. Furthermore, a sensitivity analysis was carried out by using different preference functions and higher weights for the economic criteria to examine the effect of economic factors toward the suitability results. [ABSTRACT FROM AUTHOR]

Brazil has a continental proportion where many regions have limited access to basic services to guarantee life quality, such as electricity. The universalization of access to electricity is a challenge for remote areas with difficult access to the electrical distribution lines. Energy security modeling offers technological and governance solutions. Our paper presents a script for Google Earth Engine to identify suitable areas for photovoltaic microgrids and a worksheet to calculate the weights of criteria according to the Analytic Hierarchy Process method. The script was applied to a case study in the Taquari Watershed. The Digital Elevation Model of the basin with spatial resolution of 30 meters was used to calculate its solar power generation suitability. The Taquari Watershed has 50% of its area highly suitable for solar power plants installation. Solar radiation ranged from 2.5 to 7.8 kWh.m−2.day.−1. This research presents an analysis that is highly reproducible for larger areas or other countries due to using globally available datasets, providing decision-making tools to solve problems regarding energy security, tackling water-food-energy threats to remote communities and strengthening the sustainability of territorial planning dynamics. [ABSTRACT FROM AUTHOR]

The fuzzy set theory as one of the key agents of artificial intelligence has been used to deal with vagueness and imprecision during the decision-making process. The software requirements selection is a multicriteria decision making problem which has a key importance for several software development companies. Few methods have been developed to select the software requirements from the list of the elicited requirements using fuzzy analytic hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) methods. Based on our review, we found that little attention is given on the comparison between the fuzzy AHP and fuzzy TOPSIS methods in the context of the software requirements selection problem. To address this issue, this paper presents a comparative analysis of fuzzy AHP and fuzzy TOPSIS methods by considering the small and large set of requirements of an institute examination system based on the following factors: agreement measure, time complexity, rank reversal issue, and number of judgments by decision makers. Based on the comparative study, we found that both fuzzy AHP and fuzzy TOPSIS methods produce the same set of functional requirements based on agreement measure metric in both dataset-1 and dataset-2. Fuzzy AHP requires less time to generate the ranking order in dataset-1; and fuzzy TOPSIS performs better then fuzzy AHP in dataset-2. Fuzzy AHP causes the rank reversal issue; and there is no rank reversal issue in fuzzy TOPSIS and it produces the consistent results. Fuzzy TOPSIS requires less judgment by decision makers then fuzzy AHP. Finally, we discuss the future research directions in the area of SRs selection problem. [ABSTRACT FROM AUTHOR]

China is facing the challenge of high building energy consumption, especially for rural housing, because of the backward construction technology. This issue could be solved by net-zero energy rural housing. Therefore, the passive energy-saving procedures and energy-efficient building service systems of rural housing are needed to be studied apart from renewable energy adoption. Older people with unique thermal acceptability and adaptability become the primary residents in Chinese rural buildings, which calls for the redefinition of the indoor environment. This paper firstly conducted an overall questionnaire about the indoor environment sensation and expectations of the rural elderly in Sichuan province. Field surveys and measurements were carried out in a typical self-built rural house to investigate the thermal comfort of the local order people and the indoor thermal environment variations. Furthermore, the fuzzy analytic hierarchy process was used to propose a three-layer assessment model for the rural elderly living environment to find retrofit strategies. Results showed that: (1) the thermal environment of rural buildings could not meet the thermal comfort range of older people in summer. (2) The adaptive coefficient (λ) in the adaptive Predicted Mean Vote model was 0.065 for the rural elderly, which was lower than the value of 0.21 in the Chinese standard, indicating their poor thermal adaptability. (3) The summer living environment evaluation was "A little bad", and the most effective optimization method was to decrease the indoor temperature. (4) Based on the thermal comfort of older people, architectural and construction optimizations were proposed, which could achieve an energy-saving of 52.15 %, contributing to net-zero energy rural housing. • Environment improvement and energy saving of rural housing were studied. • The age-based metabolic rate of the elderly was proposed in aPMV. • The adaptive coefficient for the rural elderly was 0.065. • The evaluation model of rural living environment satisfaction was built by FAHP. • Passive retrofit procedures were proposed to achieve NZERH. [ABSTRACT FROM AUTHOR]

In this paper, the ecological quality of Singrauli sub-district over a decade was investigated based on images of IRS LISS III and Landsat series of 2005, 2010 and 2015 respectively. The Analytic Hierarchy Process (AHP) was employed to develop the Geo-Spatial Ecological Impact Index (GEII) by assigning weights to the five ecological parameters (vegetative cover, moisture content, built-up index, water index and Land Surface Temperature (LST) and to determine the degree of impact on each one due to the increased anthropogenic activities. The study concluded that, there was an increase in the built up and the overall LST by 6.24 °C whereas, the vegetation covers and moisture content has decreased during the years 2005 to 2015. Aggregate change in ecological quality can be inferred from the increasing mean of GEII values from 3.39 to 3.61 indicates deteriorating ecological quality. The predicted map of GEII 2025 prepared using artificial neural network (ANN) revealed that the high ecological impact zones will cover 37.95% of the area by 2025. The result obtained from the study can be useful for policy and decision makers for sustainable development of urban sectors and natural resource management of the area with respect to ecological impact assessment. [ABSTRACT FROM AUTHOR]

Now that the coronavirus epidemic continues, hospitals have made a series of control measures, which makes the already relatively backward, slow traffic system around the large hospitals in the old city face more severe problems. This paper, based on the analysis of the current issues of slow traffic in large hospitals in old urban areas, according to the elements affecting slow traffic and the needs of slow traffic around hospitals, safety, accessibility, diversion, convenience, and comfortableness are used as the first level indicators, the index weights are determined by applying Analytic Hierarchy Process, and the comprehensive evaluation model of slow traffic around large hospitals in the old city is constructed by using Extentics. Through the case study, the scientific and practicality of the method is verified, which provides a scientific way for the safe and efficient operation of the slow traffic system around the large hospitals in the old city under the present epidemic control. [ABSTRACT FROM AUTHOR]

Complex environments, conflicting criteria, uncertainties, and inaccurate information are some characteristics of many nowadays real-world decision-making problems. The Multi-Criteria Decision-Making (MCDM) methodology is one of the most used, perhaps because it drives decision-making processes to be more rational, efficient, and effective. Thus, the Armed Forces of several countries have used MCDM methods in the Life Cycle Management of Defense Systems (LCM-DS) to deal with military systems' complexity, breadth, and sensitivity. However, despite the rich and vast literature available on several MCDM methods applied to LCM-DS problems, there is a lack of a recent bibliometric study on this relevant subject. This paper presents an analysis of a quantitative approach based on bibliometric metrics to evaluate the application of MCDM methods in LCM-DS. By using the Scopus and Web of Science databases as references, this study focuses on the identification of the following aspects related to the research in this field: distribution of scientific publications, most relevant sources, interaction dynamics among these sources, most prominent subjects in recent research (trend topics), and application of MCDM methods in LCM-DS. Regarding the latter, this study identified the Analytic Hierarchy Process (AHP) as the most used method in the LCM-DS since almost a quarter of the analyzed works applied it in the original, adapted, or hybrid (combined with other methods) format. Finally, our results show that MCDM methods are commonly applied to LCM-DS problems in all life cycle stages, mainly in development, utilization, and support. [ABSTRACT FROM AUTHOR]

In addition to large-scale environmental benefits, geothermal resources are nowadays expected to deliver an endogenous competitive advantage. The aim of this paper is to investigate this phenomenon for Poland. Since geothermal resources are of an endogenous nature, we assume their competitive advantage character for eleven selected municipalities in Poland. A municipality competitiveness model is built using an expert method. Panel data analysis is used to estimate four models of geothermal competitiveness. A sensitive analysis examines if the results are dependent on the model we developed. All four model scenarios are robust. The results show that the geothermal estimators significantly impact the created municipality competitiveness indicator. The geothermal energy production and geothermal bathing centres are both significant elements of municipality competitiveness in Poland. Therefore, this paper provides an argument for further expansion of the extraction of the available geothermal resources in Poland. • The assumption that geothermal energy is a local competitive advantage. • Geothermal parameters reveal high relation with indicators of local competitiveness. • Municipality competitiveness index growth is impacted in 45% by the geothermal GJ production. • Geothermal bathing centres raise by 20% the local competitiveness index. • Scale of geothermal GJ production determines the local competitiveness. [ABSTRACT FROM AUTHOR]

Hydrogen production from renewable energy sources appears to be an interesting solution for reducing greenhouse gas emissions and ensuring the energy security supply. This paper develops an integrated framework to evaluate land suitability for hydrogen production from solar energy site selection that combines multi-criteria decision making (MCDM) with geographical information systems (GIS); an application of the proposed framework for Algerian country. In GIS two types of criteria will be taken: constraints and weighting criteria. Constraints criteria will make it possible to reduce the area of study by discarding those areas that prevent the implementation of installing solar hydrogen production systems. These criteria will be obtained from the legislation (land use, water bodies, waterways, roads, railways, power lines, and also their buffer around them). Weighting criteria will be chosen according to the objective to be reached, in this case they will be the hydrogen demand, potential solar hydrogen production, digital elevation models (DEMs), slope, proximity to roads, railways, and power lines. Through the use of MCDM the criteria mentioned will be weighted in order to evaluate potential sites to locate a solar hydrogen production installation system. Analysis and calculation of the weights of these criteria will be conducted using Analytic Hierarchy Process (AHP). As a result, the final index model was grouped into four categories as "very low suitability", "low suitability", "moderate suitability" and "high suitability" with a manual interval classification method. The results indicate that 10.34% (246,272.02 km2), of the study area has very low suitability, 60.75% (1,446,907.65 km2) has low suitability, 6.68% (159,100.3 km2) has moderate suitability and 0.49% (11,669.21 km2) has high suitability for a solar-powered hydrogen production installation system. The other 21.74% (517,790.5 km2) of the study area is not suitable for such projects. The sensitivity analysis highlights that the suitable sites for solar hydrogen production installation system are dependent on the weights of the criteria that influence the decision. The MCDM methodology integrated with GIS is a powerful tool for effective evaluation of the solar-powered hydrogen production sites selection. • The paper addresses the problem of site selection for solar hydrogen projects. • Land suitability index is computed to determine the best sites. • MCDM coupled with GIS is a powerful tool for effective evaluation of the solar hydrogen production sites selection. [ABSTRACT FROM AUTHOR]

• A new method to evaluate laboratory safety management based on machine learning was proposed. • Fuzzy Analytic Hierarchy Process (FAHP) has good applicability for laboratory safety management evaluation. • The model was easy to operate and has a good application value for ensuring the personal and property safety of laboratory users. This paper proposes a new method to evaluate laboratory safety management based on machine learning that aims to address the shortcomings of traditional laboratory safety evaluation methods, including poor accuracy, large influence of human factors, and lack of a unified evaluation system. In this paper, the safety data of laboratories in Southwest University were collected using a safety checklist, and the weight of each factor affecting laboratory safety was analyzed using a Fuzzy Analytic Hierarchy Process (FAHP). The simulation results showed that the model gave a more accurate and reasonable safety risk level of the laboratory, verified the rationality and feasibility of the established method, and realized potential loopholes in the process of laboratory management and college students' operations. According to the evaluation results, the machine learning principle and the existing maintenance knowledge of the evaluation knowledge base are applied to provide effective measures and suggestions for users to complete the process of risk assessment. Through risk assessment, the professional skill and the incident control could be improved. The model was easy to operate and has a good application value for ensuring the personal and property safety of laboratory users. [ABSTRACT FROM AUTHOR]

There are three major applications (portable, stationary, transportation) of hydrogen energy (HE), and each application play a unique and important role in the sustainable development of energy system. In different regions within a country, different applications of HE are preferred. This paper therefore explores the process to decide the optimal region to develop each of the three subtypes of HE applications. To this end, the Analytical Hierarchy Process (AHP) and a fuzzy Technique the Order of Preference by Similarity to Ideal Solution (TOPSIS) method are used in the present study. Based on a literature review and in-depth interviews with officers, experts, the managers of HE-related enterprises, and consumers, the present study comes up with two selection criteria, namely, the acceptance on the applications of hydrogen energy (i.e., market entry barriers and customer's acceptance), and the integrity of hydrogen energy industrial chain on three applications (i.e., production stage, distribution stage, and marketing stage). This paper uses a case study to explore the functioning of three applications of hydrogen energy in the industrial, cultural and restricted residence regions. Four main findings emerges from this study: (1) the market structure of the portable, stationary and transportation application of HE should be pure competitive, oligopolistic, and monopolistic competition respectively; (2) the customer's acceptance for different applications is different, due to different neighborhood concerns about the quality of life; (3) the cost and benefit of different applications depend on different factors, including government policy, technological improvements and social preferences; (4) in order to promote all HE applications, the process to decide the optimal region to develop a specific HE application depends on the comparative advantages of the application. • Optimal multiple selections process for fostering applications of hydrogen energy were explored. • One of the selection criteria is the acceptance of the applications of hydrogen energy. • The other selection criterion is the integrity of hydrogen energy industrial chain. • The optimal solutions depend on the comparative advantages of different applications and regions. [ABSTRACT FROM AUTHOR]

• Simulator experiments are applied to testify the established assessment method. • Sensitivity analysis is used to prove the effectiveness of the method. • The proposed assessment method has a better sensitivity and prediction accuracy. Situation awareness (SA) reliability of operators is an important component of human reliability analysis (HRA) in digital nuclear power plants (NPPs). Therefore, how to identify effectively and reliably the risk of SA errors is of great significance for SA error prevention and risk reduction. SA reliability assessment model or method based on fuzzy logic and analytic hierarchy process (AHP) is forwarded in the first paper. In order to prove its effectiveness and reliability, sensitivity analysis and simulator experiments are applied to testify our model in this paper. The results show that the proposed assessment model of SA reliability has a certain degree of sensitivity as well as an accuracy of prediction, and there are a strong correlation and consistency between the predicted value from fuzzy inference system and the real value (or observed value) from simulator experiments. Although there are some differences between the predicted value and the real value based on the perspective of HRA, the model can be used to predict SA error probability or SA reliability within the range of 10 error factors as well as provide data and theoretical support for SA reliability assessment. [ABSTRACT FROM AUTHOR]