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Nowadays, Energy has become one of the most important issues. Negative environmental effects of fossil fuels lead countries to use renewable and sustainable energy sources day by day. In addition, energy supply and security have been an motivator factor in this field. This study focus on biomass that renewable and sustainable energy source. According to studies in literature, energy production from biomass resource less than other energy sources. The most important reason for this is the logistics costs. Therefore, biomass supply chain optimization is an important issue. In this study, mathematical models of biomass supply chain are reviewed. When the studies are evaluated, there are three approaches in modeling biomass supply chains. These approaches are as follows: 1) Collection and Distirubiton, 2) Selection, 3) Clustering. In additon, researchers generally focus on single-aim mixed integer mathematical models. However, recently, it is seen that there are multi-aim models in the literature for minimizing emissions as well as supply chain costs. In this study, general information about biomass and biomass supply chain, studies of in this area, mathematical models, details of published papers are given. Objective functions, cost/income items, methods of these models are discussed in detail. [ABSTRACT FROM AUTHOR]

Nowadays, supply chain (SC) decentralised decision making is the most usual situation in SC operations planning. In this context, different companies can collaboratively plan to achieve a certain level of individual and SC performance. However in many cases, there is reluctance to collaborate because it is not known a priori which benefits will be reported. This paper aims to develop a mathematical programming-based methodology for the evaluation of different supply chain collaborative planning scenarios (MPM-SC-CP). It is assumed that different SC decision centres (DCs) make decisions based on mixed and integer linear programming models. Two main inputs feed the proposed MPM-SC-CP, a framework and associated methodology that support the integrated conceptual and analytical modeling of the SC-CP process in which several DCs make decisions according to spatio-temporal integration. Finally, an application to a real ceramic SC was conducted. [ABSTRACT FROM AUTHOR]

Purpose: This paper studies a 3-dimensional pallet loading problem considering interlock stacking pattern, box dimensions, humidity, and storage time, where overlapping and overhanging are not allowed. Despite the importance of this problem in the literature, our work provides the first method that considers the environmental conditions such as 1) storage time and 2) humidity, and their tremendous impacts on the strength of the boxes, as has been observed widely in the DHL supply chain. Design/methodology/approach: This paper proposes a two-phase heuristic algorithm to solve a 3-dimensional pallet loading problem under real conditions (relative humidity, and storage time) considering interlock stacking patterns, where overlapping and overhanging are not allowed. In phase 1, the horizontal layer configuration is determined by block techniques. Three types of horizontal layers are created based on box dimensions perpendicular to the base. In phase 2, a novel mathematical model is propounded to improve the pallet volume utilization, and stability considering the pallet's maximum allowable height and weight, and the dynamic compression strength of boxes. The dynamic compression strength of boxes is calculated by the modified McKee formula. Two performance measures, pallet volume utilization, and stability (load height) are utilized to evaluate the performance of the proposed heuristic algorithm in real-world instances (DHL Supply Chain). Findings: The results illustrated that the dynamic compression strength of boxes decreases as the relative humidity and storage time increase. The load height changes dynamically along with box dimensions, box alignment, direction, relative humidity, and storage time. Increasing relative humidity and storage time and applying an interlock stacking pattern reduce the pallet utilization, however, enhance the pallet stability. Finally, the proposed heuristic algorithm's efficacy increases as the identical box dimensions' heterogeneity increases. Originality/value: It is believed in the supply chain where these characteristics are observed, the implementation of the heuristic algorithm will help them improve the pallet volume utilization and stability. [ABSTRACT FROM AUTHOR]

This paper provides a synthesis of the concept of supply chain optimization. The aim of the research is to identify a supply chain optimization process, the key aspects in carrying out this process, and at the same time to emphasize the advantages that the optimization of companies' processes brings through the mathematical modeling of logistic processes that can be useful in the optimization of supply chains. In the research methodology it is used the Simplex transport algorithm. In a practical situation of a company with 3 warehouses and 4 clients, it allowed optimizing the transport routes and getting a minimal total cost for logistical delivery. [ABSTRACT FROM AUTHOR]

In the supply chain environment, agile distribution refined the division of operations, responded quickly to the customer needs of the mobile terminal, and promoted the construction of an intelligent logistics distribution system. In order to integrate the distribution resources of the distribution system of the logistics industry and maximize the overall benefits of distribution, this paper designs an intelligent logistics agile distribution model and optimizes the distribution strategy. Firstly, this paper puts forward a rationalization evaluation system based on the established logistics agile distribution model. Make full use of the fuzzy subsets of each level to quantify the fuzzy indexes to evaluate, and then comprehensively clarify the index attributes through the fuzzy transformation criteria to obtain the evaluation results. Secondly, aiming at the networked agile distribution organization form, the scientific location mathematical model of agile distribution center and the path mathematical model of the agile distribution are established. Finally, the uncertain influence of many objective conditions on distribution agility has been analyzed, and the dynamic optimization model of an agile distribution path with the concept of time window under random demand is constructed. Through the experimental analysis, the rationalization evaluation strategy and index of verification test results show that the model has significant optimization advantages, which not only improve the rationality and economic benefits of distribution, but also meet the time requirements of all users. [ABSTRACT FROM AUTHOR]

• The model allocates safety stocks in supply chains at minimum cost. • An MIQCP reformulation with piecewise approximation greatly improves computational efficiency. • The piecewise function yields an improved estimation for the fill rates. • The GSM is extended to handle non-normally distributed demands. • Real-world case studies solved to optimality within few seconds of computational time. This paper presents a Multi-Echelon Inventory Optimization (MEIO) framework, based on the Guaranteed-Service Model (GSM), to allocate safety stocks across a supply chain with several locations and products, minimizing costs while meeting service level objectives. Extending previous work by Achkar et al. (2023), this paper enhances the Mixed-Integer Quadratically Constrained Program (MIQCP) with a highly efficient solution approach. The model introduces a piecewise linear approximation, significantly improving computational efficiency and the accuracy of the approximation for the fill rate function. It also introduces a different and more efficient approach to account for stochastic lead times using a discrete function. Moreover, an extension of the approach to account for non-normally distributed demands is proposed. The model is applied to several instances of a real-world case study from a pharmaceutical company, with more than 7300 product-location combinations, showing that optimal solutions can be obtained within few seconds of computational time. [ABSTRACT FROM AUTHOR]

Considering carbon emissions when making supply chain decisions has been an essential contributor for keeping this world more sustainable. This paper presents a mixed-integer linear programming (MILP) model to optimize production and transportation decision where the transportation activities involve a multimodal combination. The proposed mathematical model was aimed at mini- mizing the total costs incurred from supply chain activities as well as the emissions generated. Carbon cap is used to ensure that the emissions produced in the whole activities do not exceed the allowable limit. In this research, we address a multi- product, multi-plant, multi-departure, and arrival stations where multiple customers are to be served for multiple periods. The numerical tests show that the demand, carbon tax, and distance significantly affected the total emissions and the total costs. Interestingly, we observed that the decisions are much more affected by the logistical costs rather than the emission costs. The model presented in this paper can assist the decision makers to make production, delivery, and inventory decisions when multi-modal transportation is involved. [ABSTRACT FROM AUTHOR]

In this paper, a multi-echelon, multi-period, decentralized supply chain (SC) with a single manufacturer, single distributor and single retailer is considered. For this setting, a two-phase planning approach combining centralized and decentralized decision-making processes is proposed, in which the first-phase planning is a coordinated centralized controlled, and the second-phase planning is viewed as independent decentralized decision-making for individual entities. This research focuses on the independence and equally powerful behavior of the individual entities with the aim of achieving the maximum profit for each stage. A mathematical model for total SC coordination as a first-phase planning problem and separate ones for each of the independent members with their individual objectives and constraints as second-phase planning problems are developed. We introduce a new solution approach using a goal programming technique in which a target or goal value is set for each independent decision problem to ensure that it obtains a near value for its individual optimum profit, with a numerical analysis presented to explain the results. Moreover, the proposed two-phase model is compared with a single-phase approach in which all stages are considered dependent on each other as parts of a centralized SC. The results prove that the combined two-phase planning method for a decentralized SC network is more realistic and effective than a traditional single-phase one. [ABSTRACT FROM AUTHOR]

As the people are becoming conscious about protection of the environment from pollutant caused by human beings, businesses are adopting green technology to procure green products to save the environment from pollution. Consequently, it is a challenging task at the firm manager to capture the market providing best green quality at fair price in a given economy. The paper plans to discuss two situations in two models. In model 1, the optimal green quality and sales prices of the manufacturer and the retailer in both decentralize and centralize systems of a two-echelon supply chain system are investigated. The profit functions of the manufacturer and the retailer include procurement costs, selling prices and cost for green level development and then it is analyzed by calculus method to obtain the optimal values of the decision variables. The model 2 focuses on price competition of two substitute products where demand of the end customers depends on price and quality of green product. Both the firms of green and regular products manufacturer are corporate social responsible. In this model, profit functions of the firms 1 & 2 are formulated separately considering revenues from sales items, cost of green quality and contribution for activities of social responsibility. The main objective is to find out optimal prices and green quality in order to maximize the profit functions of individual and integrated systems. The proposed models are analyzed mathematically and numerical examples are illustrated to justify the feasibility of the model in reality. [ABSTRACT FROM AUTHOR]

Due to increasing air pollution, which is a consequence of the environmental effects of production in various industries, green supply chain management (GSCM) has attracted the attention of both scholars and practitioners. Green supplier selection is an important problem in GSCM and seeks to satisfy a firm's environmental goals as well as its economic targets. In this paper, for the first time, a green supplier selection problem considering both green and non-green evaluation criteria in a closed-loop supply chain is studied, and a cap-and-trade mechanism as a way of controlling the air pollution caused by manufacturers is proposed. To solve this particular problem, we propose a multi-objective robust optimization (RO) model. This specific model is an effective approach to handle uncertainty. A numerical example using randomly generated data, accompanied by subsequent discussion of the proposed approach, is deployed to validate the model. The results prove that the developed model for green supplier selection is able to effectively enhance the decision-making process of the experts. By illustrating the trade-off in robustness between the model and proposed solutions, as well as the effect of the deviation penalty on the closeness of results to the achieved solution, we show how firms can make optimal decisions when assigning the parameters. Furthermore, analyses show that decreasing the allowance amount (cap) and increasing the allowance prices in the cap-and-trade system escalate the firms' costs, but lower the amount of carbon released. Finally, we show that the cap-and-trade mechanism results in a better solution in terms of the total utility of the supply chain compared to the penalty-based system for a specific range of carbon allowance. • This paper generalizes the green supplier selection and order allocation problem. • A mathematical model for the problem is developed. • A robust optimization approach to handle the model uncertainty is developed. • The impact of changes in model parameters on the objective functions is analyzed. • The cap-and-trade mechanism is compared with a penalty-based mechanism. [ABSTRACT FROM AUTHOR]

Sustainable Supply Chain Management (SSCM) is a topic of growing interest among researchers. Many works have investigated the negative impact of CO2 emission, but have put less emphasis on other emission types. Many works have focused on the economic and environmental dimensions of sustainability but lacked content on the social dimension. Since SSCM is concerned with all aspects of sustainability, this work undertakes the three dimensions of sustainability and models particulate pollution (PM2.5) which has been cited in the literature to have a negative impact on human health. The paper constructs a mathematical programming model that minimizes the transportation costs and the undesirable social medical costs for remedying the release of PM2.5 into the atmosphere. The paper solves a model that evaluates different transportation modes, transportation costs, carbon emissions, PM2.5, medical costs, and capturing options. Moreover, the work utilizes a Monte Carlo simulation to best present the inherent variations in the model. Largely, the work provides stakeholders with transportation mode choices and greening opportunity investments to minimize the overall transportation costs while respecting physical and operational constraints. [ABSTRACT FROM AUTHOR]

• We develop a mathematical programming model for scheduling turnaround maintenance activities for a network of plants in a supply chain. • We propose a heuristic algorithm for solving the model when the network has large number of plants. • A case study petrochemical supply chain is used to demonstrate the utilization of the model and the effectiveness of the heuristic. Turnaround (TAM) is a periodic maintenance in which plants are shutdown to conduct inspections, repairs, preventive maintenance and overhauls. The shutdown periods range from three to four weeks and prolonging this period is expensive and therefore requires effective planning. The primary purpose of this paper is to develop a mathematical programming model to coordinate and plan TAM for several plants in an integrated supply chain network. A secondary objective is to develop a heuristic algorithm for solving the model when the network has large number of plants. The model and the algorithm are developed, tested and applied on a case study petrochemical supply chain. The exact algorithm takes 8.3 times the time of the heuristic. In addition the heuristic algorithm provides near optimal solution in much shorter time. The developed model provides a tool to plan TAM for several plants in an integrated supply in an optimal fashion. [ABSTRACT FROM AUTHOR]

In this paper, a bi-objective mixed-integer linear programming model is formulated for designing a perishable pharmaceutical supply chain network under demand uncertainty. The objectives of the proposed model are to simultaneously minimize the total cost of the network and lost demand amount. The proposed model is multi-product and multi-period and includes simultaneous facilities location, vehicle routing, and inventory management; hence, it is considered an operational-strategic model. Procurement discounts, the lifetime of products, storing products for future periods, lost demand, and soft and hard time windows are the main assumptions of the proposed model. A novel hybrid approach, based on fuzzy theory, chance constrained programming, and goal programming approach, is developed for solving the proposed bi-objective model. The validity of the proposed model and developed solution approach is evaluated using data from Avonex, a prefilled syringe distribution chain serving 11 health centers in Tehran. The proposed model indicates that some lost sales exist, and to overcome the lost sales, the case company needs to invest a little more in addition to the initial investment of around 2 billion tomans. The results obtained from implementing the model and the sensitivity analysis, using real-world data, confirm the efficiency and validity of the proposed mathematical model and solution approach. [ABSTRACT FROM AUTHOR]

This paper proposes a production and differential pricing decision model in a two-echelon supply chain that involves a demand from two or more market segments. In this framework, the retailer is allowed to set different prices during the planning horizon. While integrated production-marketing management has been a key research issue in supply chain management for a long time, little attention has been given to set prices and marketing expenditures in integrated multi-site (parallel) manufacturing systems and multiple demand classes. Generally, the presence of multiple demand classes induced by different market segments may impose demand leakage and then change production plan and ordering policies throughout the supply chain system. To tackle this problem, this paper develops a novel approach in order to provide an optimal aggregate production and marketing plan by interconnecting the sales channels of the retailer and demand. A non-linear model is established to determine optimal price differentiation, marketing expenditures and production plans of manufacturing sites in a multi-period, multi-product and multi-sale channels production planning problem by maximizing total profit of the supply chain. To handle the model and obtain solutions, we propose an efficient analytical model based upon convex hulls. Finally, we apply the proposed procedure to a clothing company in order to show usefulness and significance of the model and solution method. [ABSTRACT FROM AUTHOR]

This paper addresses the multiobjective, multiproducts and multiperiod closed‐loop supply chain network design with uncertain parameters, whose aim is to incorporate the financial flow as the cash flow and debts' constraints and labor employment under fuzzy uncertainty. The objectives of the proposed mathematical model are to maximize the increase in cash flow, maximize the total created jobs in the supply chain, and maximize the reliability of consumed raw materials. To encounter the fuzzy uncertainty in this model, a possibilistic programming approach is used. To solve large‐sized problems, the multiobjective simulated annealing algorithm, multiobjective gray wolf optimization, and multiobjective invasive weed optimization are proposed and developed. The numerical results demonstrate that these algorithms solve the problems within about 1% of the required solving time for the augmented ε‐constraint and have similar performance and even better in some cases. The multiobjective simulated annealing algorithm with a weak performance takes less time than the other two algorithms. The multiobjective gray wolf optimization and multiobjective invasive weed optimization algorithms are superior based on the multiobjective performance indices. [ABSTRACT FROM AUTHOR]

This paper aims to develop a recovery planning approach in a three-tier manufacturing supply chain, which has a single supplier, manufacturer, and retailer under an imperfect production environment, in which we consider three types of sudden disturbances: demand fluctuation, and disruptions to production and raw material supply, which are not known in advance. Firstly, a mathematical model is developed for generating an ideal plan under imperfect production for a finite planning horizon while maximizing total profit, and then we re-formulate the model to generate the recovery plan after happening of each sudden disturbance. Considering the high commercial cost and computational intensity and complexity of this problem, we propose an efficient heuristic, to obtain a recovery plan, for each disturbance type, for a finite future period, after the occurrence of a disturbance. The heuristic solutions are compared with a standard solution technique for a considerable number of random test instances, which demonstrates the trustworthy performance of the developed heuristics. We also develop another heuristic for managing the combined effects of multiple sudden disturbances in a period. Finally, a simulation approach is proposed to investigate the effects of different types of disturbance events generated randomly. We present several numerical examples and random experiments to explicate the benefits of our developed approaches. Results reveal that in the event of sudden disturbances, the proposed mathematical and heuristic approaches are capable of generating recovery plans accurately and consistently. [ABSTRACT FROM AUTHOR]

[Display omitted] • This paper considers quality integration in a coordinated model of project scheduling and material transportation. • This model coordinates quality concepts in internal processes, customer-related processes, and supplier-related processes. • In this study, we assume that both renewable and non-renewable resources influence the quality of project activities. • In our model, material transportation is modeled using MDOVRP to meet the needs of project-oriented organizations. This study aims to investigate how quality integration affects a joint model of multi-project scheduling and material transportation. Therefore, the research problem not only considers the quality of project activities, but also focuses on quality in processes related to suppliers and customers. Accordingly, this study considers the quality of materials as a factor when determining the suppliers in a project-based organization. Furthermore, unlike the existing studies, it also assumes that the rework-time of projects depends on the quality of materials. The research problem is addressed using a mixed integer linear programming model, which minimizes the total normalized cost (TNC) as a measure of the balance between supply chain costs. Contrary to previous models, this model examines the simultaneous impacts of renewable and nonrenewable resources on project quality. Also, the material transportation is modeled based on the "multi-depot open vehicle routing problem" to increase the model's applicability in real conditions. In order to solve the research problem, a tabu search algorithm is applied, which is verified based on instances of different sizes. Then, the proposed model is compared with one of the similar models in the literature to determine its efficiency. Additionally, a real-world case study is utilized to show the model application. The results show that the quality concept in the suggested model leads to more appropriate materials and shorter routes for transportation. Therefore, quality integration in this model reduces the total normalized cost by improving projects' delays and transportation costs. [ABSTRACT FROM AUTHOR]

A large number of criteria, the very diverse use of terminology and different classifications of criteria used to select a logistics service provider (LSP) reflect the lack of consensus in defining criteria. Moreover, whether the criteria are consistent with external requirements has not been analysed, which are vitally important for the success and competitiveness of the supply chain. This paper therefore presents a carefully prepared and evaluated classification system of criteria aligned with the requirements of the external environment. A multi-stage methodological approach was used. Selection criteria obtained from the systematic review of literature were first carefully analysed to find potential shortcomings. After that, a cluster method was used to reduce the number of criteria and to aggregate similar criteria. A Pareto analysis (75/25 rule) was further used to rank the criteria according to their frequency of use and consequently according to importance. The obtained categories of criteria (vitally important criteria (C1), very important criteria (C2), important criteria (C3) and less important criteria (C4), using the AHP method, were compared by the experts to define their weights. This paper summarizes and extends the recent literature through a six-step methodological approach and proposes a new classification system of selection criteria. [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]

In a network the nodes represent stations, warehouses, distribution centers and customers and not just materials but also information circulate, so the minimum cost flow model, that only takes transport costs into account is one of the tools used to support the decision-making. In reality, the nodes provide a service which requires a service time, the servicing follows a discipline and also a queue is formed, generating the respective service and queuing costs. A modified version of the minimum cost flow model is proposed in this paper for the optimization of the flow in a queuing network. A variety of cases were solved. An acceptable level of accuracy was observed in the calculation of the time cycle and work in progress. The results indicate that the optimum solution tends to balance the workload along the network. This paper is of interest to administrators and people in charge of supply chains and is useful for decision-making in the medium or long time. [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]

Highlights • We model a new quantity discounts supply chain planning problem. • The model is very hard to solve using leading commercial solvers. • We develop MIP-based local search algorithms for our problem. • We apply our model to a realistic food supply chain. • We show the efficiency of our algorithms in getting high quality solutions quickly. Abstract Supplier selection with quantity discounts has been an active research problem in the literature. In this paper, we focus on a new real-world quantity discounts scheme, where suppliers are selected in the beginning of a strategic planning period (e.g., 5 years). Monthly orders are placed from the selected suppliers, but the quantity discounts are based on the aggregated annual order quantities. We incorporate this type of cost structure in a multi-period, multi-product, multi-echelon supply chain planning problem, and develop a mixed integer linear programming (MIP) model for it. Our model is highly intractable; leading commercial solvers cannot construct high quality feasible solutions for realistic instances even after multiple hours of solution time. We develop an algorithm that constructs an initial feasible solution and a large neighborhood search method that combines two customized iterative algorithms based on MIP-based local search and improves such solution. We report numerical results for a food supply chain application and show the efficiency of using our methodology in getting very high quality primal solutions quickly. [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]

In today's business world, oil companies cannot be productive and competitive, and thus, will not survive without taking the supply chain management concepts into account. Consequently, the management of a crude oil supply chain (COSC) is increasingly receiving substantial importance. The growing number of papers and books on this topic is a further witness of this fact. To foster insight into issues intertwined with COSC problems, this paper is devoted to an extensive review of mathematical programming models in this context. The classification approach for this review is based on a taxonomy framework. In this framework, ongoing and emerging challenges surrounding the strategic and tactical decisions of COSC problems are investigated. As a main goal, the gaps of literature are analyzed to recommend possible research directions. [ABSTRACT FROM AUTHOR]

A mission of the Learning Factory (LF) is a development of practice-based engineering curriculum through the simulation of a real factory by specialized equipment. In this paper, supply chain network simulator is developed, as a replacement for the traditional board Beer Game. The board Beer Game could be misused by participants in order to avoid significant bullwhip effect, which occurrence is the Beer Game main aim. The disadvantage of the board Beer Game, that participants have insight in inventory levels and placed orders and thus strategically act upon their knowledge or even activate a sort of decentralized information sharing policy, is avoided. Further considerations prove the mandatory occurrence of bullwhip effect without decentralized information sharing policy on three case studies. Optimal mathematical model for placing orders within a supply chain was defined according to multi-criteria optimization process using spreadsheet simulation. As even optimal model results with the bullwhip effect, newly developed system will always lead to the tremendous bullwhip effect during the learning process. [ABSTRACT FROM AUTHOR]

The paper considers a three-echelon supply chain which consists of one supplier, one manufacturer and one retailer for trading a single product. The market demand at the retailer is influenced by the retail price and the quality of the product. The quality of the finished product at the manufacturer depends on the supplier’s raw material quality. We analyze the model for both deterministic and stochastic demand patterns. We first study the centralized and decentralized systems, and then the decentralized system with a sub-supply chain coordination strategy (where the manufacturer chooses to merge with either the supplier or the retailer and then acts as a single entity) and the two-level retail fixed mark-up (RFM) strategy. In the case of the two-level RFM strategy, the manufacturer and the retailer use fixed mark ups over the supplier’s wholesale price. The proposed models are demonstrated through numerical examples. It is observed from the numerical study that the two-level RFM strategy is superior to the sub-supply chain coordination strategy. Further, the two-level RFM strategy in the stochastic demand scenario is not as effective as in the deterministic demand scenario. [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]

This paper deals with a two-level supply chain comprising of single manufacturer and single retailer who sells multi-items. The units in inventory of each period are subject to deterioration at a constant rate. The manufacturer has finite production capacity and manufacturing proportional to the demand rate. The manufacturer offers credit period to the retailer. Price sensitive quadratic demand is debated here which is suitable for the items whose demand increase initially and after some time it starts to decrease. Here, comparison between independent and joint decision is studied regarding their decision variables and average profits. The classical optimization is used to optimize the total profit of the supply chain with respect to selling price and cycle time. The model is supported with numerical examples and also established best scenario and best policy of the model. Sensitivity analysis is done to deduce managerial insights. It is observed that the players are encouraged to join hand to hand to run a business by joint decisions. [ABSTRACT FROM AUTHOR]

In most supply chains (SCs), transaction relationships between suppliers and customers are commonly considered to be an extrapolation from a linear perspective. However, this traditional linear concept of an SC is egotistic and oversimplified and does not sufficiently reflect the complex and cyclical structure of supplier-customer relationships in current economic and industrial situations. The interactional relationships and topological characteristics between suppliers and customers should be analyzed using supply networks (SNs) rather than traditional linear SCs. Therefore, this paper reconceptualizes SCs as SNs in complex adaptive systems (CAS), and presents three main contributions. First, we propose an integrated framework of CAS network by synthesizing multi-level network analysis from the network-, community- and vertex-perspective. The CAS perspective enables us to understand the advances of SN properties. Second, in order to emphasize the CAS properties of SNs, we conducted a real-world SN based on the Japanese industry and describe an advanced investigation of SN theory. The CAS properties help in enriching the SN theory, which can benefit SN management, community economics and industrial resilience. Third, we propose a quantitative metric of entropy to measure the complexity and robustness of SNs. The results not only support a specific understanding of the structural outcomes relevant to SNs, but also deliver efficient and effective support to the management and design of SNs. [ABSTRACT FROM AUTHOR]

In this paper, we have proposed a dual-channel supply chain model in uncertain environment to analyze the demand of manufacturer and retailer demand in which the profit being maximized. Linguistic terms are also utilized to establish two fuzzy systems for estimating the demand in direct and retail channels. In order to do that, a mathematical model is proposed based on decentralized situation of supply chain. To solve the model, we have developed a hybrid solution method of genetic algorithm, fuzzy system, and L-P metric. Finally, several test problems are first generated; then, the computational results are analyzed. [ABSTRACT FROM AUTHOR]

This paper studied system dynamics characteristics of closed-loop supply chain using repeated game theory and complex system theory. It established decentralized decision-making game model and centralized decision-making game model and then established and analyzed the corresponding continuity system. Drew the region local stability of Nash equilibrium and Stackelberg equilibrium, and a series of chaotic system characteristics, have an detail analysis of the Lyapunov index which is under the condition of different parameter combination. According to the limited rational expectations theory, it established repeated game model based on collection price and marginal profits. Further, this paper analyzed the influence of the parameters by numerical simulations and concluded three conclusions. First, when the collection price is to a critical value, the system will be into chaos state. Second, when the sale price of remanufacturing products is more than a critical value, the system will be in chaos state. Last, the initial value of the collection price is sensitive, small changes may cause fluctuations of market price. These conclusions guide enterprises in making the best decisions in each phase to achieve maximize profits. [ABSTRACT FROM AUTHOR]

Abstract: In several recent investigations dealing with the economic order quantity with permissible delay in payments, the following assumptions are made: (A) The supplier always offers the retailer fully permissible delay in payments independent of the order quantity. (B) The annual interest which is charged per dollar in stocks by the supplier is higher than the annual interest earned on investment per dollar. (C) The unit purchase cost c is the same as the selling price s per unit. Huang [1] generalizes the concept of fully permissible delay in payments by advocating that the supplier would offer the retailer partially permissible delay in payments where the order quantity is smaller than a predetermined quantity to relax the assumption (A). Motivated essentially by Huang’s work [1], the main purpose of this paper is twofold as stated below: (P1) This paper will extend Huang’s work [1] by establishing new inventory models without having the assumptions (B) and (C) to match the real world situation. (P2) This paper will present new solution procedures different from those of Huang [1]. Among other things, these new solution procedures will show that those of Huang [1] will cause misuses under some circumstances. Several numerical examples illustrate the fact that the percentages of the cost penalty (PCP) of misuses are terribly high in some cases. [Copyright &y& Elsevier]

Holistic supply chain network (H-SCN) systems are a set of supply chains that have inter-dependence relations. Design and management of H-SCN systems are largely ignored in the literature. Modeling of H-SCN systems will provide a computational facility for design and management of H-SCN systems. A model for disruption of the H-SCN system was proposed by us before, which consists of two parts: a model for disruption of a single firm and a model for propagation of disruption. The present paper mainly discusses how these models can be implemented especially with Petri nets. Guidelines with templates of how the Petri net models for H-SCN systems can be constructed in industrial setting are also given to facilitate the use of our model. Since H-SCN systems are complex network systems, this paper may also contribute to the field of the Petri net technique for network systems modeling in the aspect of reduction of complexity arising from vast amounts of construct instances-a common problem that existed in a Petri net model. Indeed, the proposed Petri net model is suitable for any type of supply chains or supply chain networks. [ABSTRACT FROM AUTHOR]

Purpose: Optimal order allocation on the part of the buyer in a multi-supplier environment has become a major concern in supply chains. There are numerous articles that analyze and present models for optimizing order allocation from a given panel of suppliers. The purpose of this paper is to provide an analysis on this topic which considers: (i) aims, (ii) results, (iii) model complexity, and (iv) resolution procedures. Design/methodology/approach: The paper reviews twenty-eight articles, twenty-one of them published since 2007 in journals indexed by Journal Citation Reports (in ISI Web of Knowledge) on this topic. Findings: This review reveals four main aspects mentioned as determinant in generating mathematical models. The analysis of these four points does not allow for a single, overarching model. Rather, all analyzed solutions reflect and respond to a specific company environment. Originality/value: A global analysis on several recent papers, describing main aspects wich determines optimal order allocation in multi-supplier environment. [ABSTRACT FROM AUTHOR]

This paper explores the quantity discount coordination models in the fashion supply chain with uncertain yields and random demand. The paper proves that, under the independent and noncoordinated decision patterns, there exists a Nash equilibrium between the supplier and the manufacturer which reduces the supply chain's profit margin. In order to achieve the "optimal" centralized supply chain expected profit margin, new quantity discount models have been established. Both the supplier-oriented and the manufacturer-oriented Stackelberg supply chain gaming models are investigated. Our analytical and numerical analyses show that the quantity discount contract proposed in this paper can largely reduce the negative influence brought by the uncertainty of yields and demand. Therefore, the profit margin of supply chains based on quantity discount can reach the optimal level of the supply chain under the centralized setting. [ABSTRACT FROM AUTHOR]

This paper shows a multi-objectives mixed-integer non-linear programming (MINLP) model for a petrochemical supply chain under uncertainty environments, namely disruption risks and less knowledge of parameters. In this model, two efficient queuing systems are applied in nylon plastic manufacturing and recycling centers, in which a Jackson network is also used. The aims are to minimize the average tardiness to deliver products, total cost and transportation cost. In addition the developed model specifies the optimal locations for a new distribution center (DC), collection center and disposal center as well as the optimal allocation of customer zones to each DC. This model is solved in three stages: (1) a Jackson network determines the queuing parameters, (2) an Lp -metric approach makes the multi-objectives into a single objective, and (3) an efficient Lagrangian relaxation based on a sub-gradient approach solves the presented model. Additionally, a real case study is shown in details to depict the application of the presented model. At the end, the sensitivity analyses are carried out to check the optimal objectives by changing the important parameters. [ABSTRACT FROM AUTHOR]

Due to the rise in awareness of environmental issues and the depletion of virgin resources, many firms have attempted to increase the sustainability of their activities. One efficient way to elevate sustainability is the consideration of corporate social responsibility (CSR) by designing a closed loop supply chain (CLSC). This paper has developed a mathematical model to increase corporate social responsibility in terms of job creation. Moreover the model, in addition to increasing total CLSC profit, provides a range of strategic decision solutions for decision makers to select a best action plan for a CLSC. A proposed multi-objective mixed-integer linear programming (MILP) model was solved with non-dominated sorting genetic algorithm II (NSGA-II). Fuzzy set theory was employed to select the best compromise solution from the Pareto-optimal solutions. A numerical example was used to validate the potential application of the proposed model. The results highlight the effect of CSR in the design of CLSC. [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]

Forward and reverse supply chains form a closed-loop supply chain. In this paper, a mathematical model is proposed for a closed-loop supply chain network by considering global factors, including exchange rates and customs duties. The model is a multi-objective mixed-integer linear programming model under uncertain demand. A solution approach based on fuzzy programming is developed for solving the optimization problem. The model is then applied in a network, which is located in Southwestern Ontario, Canada. A sensitivity analysis is provided to validate the model. This model considers global factors, multiobjectives, and uncertainty simultaneously in a closed-loop supply chain network. [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]

Abstract: This paper is to resolve the VRPTW and the inventory control decision problem simultaneously since both the vehicle routing decision with time windows and the inventory control decision affect each other and must be considered together. A mathematical model of inventory routing problem with time windows (IRPTW) is proposed. Since finding the optimal solution(s) for IRPTW is a NP-hard problem, this paper proposes a two-phase heuristic method. The first phase is to find the initial solution. The second phase is to improve the solution adopting the variable neighborhood tabu search (VNTS) selecting better neighborhood solutions, to obtain the optimal solution. Moreover, the proposed method was compared with three other heuristic methods. The experimental results indicate that the proposed method is better than the three other methods in terms of average supply chain cost (transportation cost, time window violation penalty cost and inventory cost). [Copyright &y& Elsevier]

Abstract: In this paper, we consider the value of using Hierarchical Task Analysis (HTA) as a grammar to map actions in context. The grammar approach aims to develop a richer picture of user actions in a task accommodating aspects of the socio-organizational context. This paper reflects on user tasks as emerged from interviews with real users in supply chain industries where Forecasting Support Systems (FSS) are used to predict future product sales. In this paper, we use HTA to describe what the expert literature has identified as the stages in producing sales forecasts. In order to evaluate this against reported scenarios and observations of actual use, we apply an approach that uses a parallel to the grammar of everyday language to represent user activities. In addition to specifying the particular socio-organizational aspects of FSS use, we show how the grammar approach contributes to effective analysis of unstructured, qualitative data. The methodology we adopt also eases our attempt to understand user tasks and validate the constructed HTA model in a given context. The methodological implications and future research directions for task analysis models are discussed. [Copyright &y& Elsevier]

Abstract: Production quality in the food production supply chain is studied in this paper. The deficiencies of quality monitoring that exist in traceability systems are analyzed. An abnormality diagnosis algorithm, pre-warning method and structure of pre-warning system are presented. Four abnormal data types in supply chain are analyzed, they are substandard abnormality, over-range abnormality, abnormal distribution and abnormal tendency. All the detection data of the whole supply chain are monitored timely and pre-warned. The production abnormality of the logistics unit is diagnosed and automatically warned, and the decision support information is given. A standard hierarchy evaluation indicator system for abnormalities is developed in this paper. A mathematical model for abnormality detection is developed by combining radial base function (RBF) neural network, fuzzy control, and statistical analysis methods. This model is used in detecting and recognizing different types of abnormalities in the food production supply chain, especially hidden problems. The simulation results show that the proposed pre-warning system can effectively identify abnormal data types, and accurately determine whether a warning should be issued, depending on the warning level when an abnormality is detected by the system. The pre-warning system for food production supply chain performs well and effectively. [ABSTRACT FROM AUTHOR]

Abstract: Global enterprises require extended logistics operations that integrate channel intermediaries into the network. The method for deriving integrated models for logistics hubs that improve the efficiency of manufacturers’ global operations is the focus of this paper. Under government sponsorship, six industrial logistics hubs were implemented by leading manufacturing sectors across Taiwan over a five year period from 2004 until 2008. Each industry sector had unique industry characteristics, business strategies, and logistics models. Therefore, this paper describes how generalized and quick to implement integrated logistics hubs are developed by studying the successful reference models and systems used by six independent industrial sectors. The research results provide a field tested method for deriving integrated logistics hub models in different manufacturing economies with notes that provide sufficient methodological detail for repeating the construction of logistics hubs in other manufacturing economies. [ABSTRACT FROM AUTHOR]

Fuzzy goal programming has important applications in many areas of supply chain, logistics, transportation and shipping business. Business management has complications, and there exist many interactions between the factors of its components. The locomotive of world trade is maritime transport and approximately 90% of the products in the world are transported by sea. Optimization of maritime operations is a challenge in order to provide technical, operational and financial benefits. Fuzzy goal programming models attract interests of many scholars, therefore the objective of this paper is to investigate the problem of minimization of total cost and minimization of loss or damage of containers returned from destination port. There are various types of fuzzy goal programming problems based on models and solution methods. This paper employs fuzzy goal programming with triangular fuzzy numbers, membership functions, constraints, assumptions as well as the variables and parameters for optimizing the solution of the model problem. The proposed model presents the mathematical algorithm, and reveals the optimal solution according to satisfaction rank from 0 to 1. Providing a theoretical background, this study offers novel ideas to researchers, decision makers and authorities. [ABSTRACT FROM AUTHOR]

The paper proposes a structured model for evaluating vendor selection using the analytical hierarchy process (AHP) and fuzzy AHP. The model is developed using evidence from an empirical study. The paper aims to demonstrate how the model can help in solving such decisions in practice. A usability evaluation of the AHP-based model with three vendors is discussed. It also examines the structure of the decision hierarchy, whether it can represent vendor selection decisions in reality and whether it covers all key factors affecting vendor selection choices. The effectiveness of the AHP model is illustrated using a company in the southern part of India and the results validated using fuzzy AHP. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical model for the design of a non-cooperative supply chain where transportation activities are provided by logistics companies. We consider a four-layer network comprised of manufacturers, retailers, customers, and logistics service providers (LSPs). In this problem, manufacturers, retailers, and LSPs do not collaborate or engage in any type of bargaining strategy among one other. Instead, they compete to supply products to customers at demand markets, while each agent seeks to maximize his own profit. LSPs compete among themselves to provide logistics (transportation/warehousing) services to manufacturers. It is considered that manufacturers, LSPs, and retailers collaborate to maximize services. Normally this problem cannot be modeled as an optimization problem, so we use a variational inequality approach to formulate it. To the best of our knowledge, this important problem, which helps evaluate options and make decisions when logistics activities are provided by LSPs, has not been modeled in the literature and this constitutes our main contribution. The model determines the optimal level of production for each manufacturer, the flow of products between manufacturers and retailers, the flow of products to be handled by each logistics service provider and the flow of products between retailers and demand markets in a non-cooperative environment. Numerous experiments are presented and adapted from test examples that are available in the literature, while results and important findings are discussed. [ABSTRACT FROM AUTHOR]

In consideration of influence of loss, freshness, and secret retailer cost of products, how to handle emergency events during three-level supply chain is researched when market need is presumed to be a nonlinear function with retail price in fresh agricultural product market. Centralized and decentralized supply chain coordination models are studied based on asymmetric information. Optimal strategy of supply chain in dealing with retail price perturbation is caused by emergency events. The research reveals robustness for optimal production planning, wholesale price for distributors, wholesale price for retailers, and retail price of three-level supply chain about fresh agricultural products. The above four factors can keep constant within a certain perturbation of expectation costs for retailers because of emergency events; the conclusions are verified by numerical simulation. This paper also can be used for reference to the other related studies in how to coordinate the supply chain under asymmetric and punctual researches information response to disruptions. [ABSTRACT FROM AUTHOR]

The responsible management of product return flows in production and inventory environments is a rapidly increasing requirement for companies. This can be attributed to economic, environmental and/or regulatory motivations. Mathematical modeling of such systems has assisted decision-making processes and provided a better understanding of the behavior of such production and inventory environments. Therefore, this paper reviews the literature on the modeling of reverse logistics inventory systems that are based on the economic order/production quantity (EOQ/EPQ) and the joint economic lot size (JELS) settings, so as to systematically analyze the mathematics involved in capturing the main characteristics of related processes. The literature is surveyed and classified according to the specific issues faced and modeling assumptions. Special attention is given to environmental issues. In addition, there are indications of the need for the mathematics of reverse logistics models to follow current trends in ‘greening’ inventory and supply-chain models. Finally, the modeling of waste disposal, greenhouse-gas emissions and energy consumption during production is considered as the most pressing priority for the future of reverse logistics models. An illustrative example for modeling reverse logistics inventory models with environmental implications is presented. [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]