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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]

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]

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]

There are many materials for which the quantity needed by a firm is at best indirectly related to the quantity of final product produced by that firm, such as solvents in manufacturing processes or office supplies. For any such "indirect" materials, an inescapable incentive conflict exists: The buyer wishes to minimize consumption of these indirect materials, while the supplier's profits depend on increasing volume. Both buyer and supplier can exert effort to reduce consumption, hence making the overall supply chain more efficient. However, no supplier will voluntarily participate unless contract terms are fundamentally revised. This can be done through a variety of "shared-savings" contracts, where both parties profit from a consumption reduction. This paper analyzes several such contracts currently in use for chemicals purchasing. We show that such contracts can always increase supply-chain profits but need not lead to reduced consumption. We analyze equilibrium effort levels, consumption, and total profits, and show how these change with the contract parameters. We find that the goals of maximizing joint profits and minimizing consumption are generally not aligned. Also, surprisingly, a decrease in a cost parameter can lead to a decrease in profits; it may be necessary (but is always possible) to renegotiate the shared-savings contract to reap the benefits of a cost decrease. [ABSTRACT FROM AUTHOR]

To stay abreast of current supply-market pricing, it is common for procurement managers to frequently organize auctions among a pool of qualified suppliers (the supply base). Sole awards can alienate losing suppliers and cause them to defect from the supply base. To maintain the supply base and thereby control the high costs of finding and qualifying new suppliers, buyers often employ split awards, which in turn inflate purchase costs. This results in a trade-off that we investigate in an infinite-horizon stationary setting in which the relative cost position of each supplier is randomly drawn in every period. We characterize the optimal split award that minimizes long-run costs (purchasing and qualification) and show that maintaining a constant supply-base size--using a “qualify-up-to” policy--s optimal for the buyer. We find that neither the extent of multisourcing nor the buyer’s value of split awards compared with winner-take-all auctions are monotonic in the qualification cost and that split-award auctions can increase ex ante system, buyer, and supplier benefits simultaneously. To our knowledge, this is the first paper studying split-award auctions for supply-base maintenance, and it will hopefully galvanize further research on this important topic. [ABSTRACT FROM AUTHOR]

In this paper, we present a methodological framework for conceptual modeling of assembly supply chain (ASC) networks. Models of such ASC networks are divided into classes on the basis of the numbers of initial suppliers. We provide a brief overview of select literature on the topic of structural complexity in assembly systems. Subsequently, the so called Vertex degree index for measuring a structural complexity of ASC networks is applied. This measure, which is based on the Shannon entropy, is well suited for the given purpose. Finally, we outline a generic model of quantitative complexity scale for ASC Networks. [ABSTRACT FROM AUTHOR]

One of the advantages of sustainable competition for manufacturing systems is to make supply chain activities more efficient and effective. One of the major parts of these activities that can save a lot of costs is careful outsourcing. In this study, an approach based on decision-making policies in order to select suppliers and allocate order volume to them is introduced. The main contribution of this research is a comprehensive approach for optimizing both supplier evaluation and order allocation. In this regard, first, based on the evaluation, 39 key indicators were identified to evaluate the suppliers, and based on the content analysis, 25 key indicators were screened based on the Lavache method. Next, based on the fuzzy Delphi method, 11 indicators were selected from among the 25 key effective indicators. Finally, the Best-Worst Method (BWM) and a robust multi-objective formulation are proposed to find the weight of the effective criteria and the optimal order allocation to suppliers, respectively. Moreover, it is proved that the company under study faces a variety of suppliers and there is a need to analyze key indicators such as exchange rate changes and ease of communication. Based on the BWM results, it was shown that the exchange rate change trend with a weight of 0.24 is in the first place, and the quality system support index with a weight of 0.12 is in the second place. Moreover, based on the results of the proposed robust multi-objective mathematical model, it was revealed that in order to maintain the resilience of suppliers, the total demand should be distributed among all suppliers and the second supplier with a volume of 3600 units of raw materials has the largest share in delivering the required demand. [ABSTRACT FROM AUTHOR]

This paper considers a two-level supply chain coordination problem for fixed lifetime products with permissible delay in payments. Two cases are discussed; that is, the retailer is required to settle the balance before the end of the ordering cycle (Case I) and after the ordering cycle (Case II). The coordination models are proposed and analyzed, respectively. The analytical methods as to how to determine the optimal policy are presented. In addition, it is indicated that the supplier's cost as well as that of the total system will be reduced no matter how much the parameters change, and the retailer will benefit from coordination, if the supplier is willing to share the cost saving with him/her in Case I. In Case II, the retailer's average cost will be reduced and the supplier will benefit from coordination only under certain conditions. Besides, the results show that, for fixed lifetime products, providing longer credit period than the retailer's order period is not commonly applicable. [ABSTRACT FROM AUTHOR]

Abstract: An organization's environmental performance is affected by its suppliers' environmental performance, and selecting green suppliers is a strategic decision in order to be more competitive in today's global market. The supplier selection problem involves several quantitative and qualitative criteria. In the supplier selection process, if suppliers have limited capacity or other constraints, it is necessary to determine the best supplier and order quantity of each supplier. In this paper, we present an integrated approach, of fuzzy multi attribute utility theory and multi-objective programming, for rating and selecting the best green suppliers according to economic and environmental criteria and then allocating the optimum order quantities among them. At first, the fuzzy analytic hierarchy process and fuzzy technique for order preference by similarity to ideal solution is applied in order to analyze the importance of multiple criteria by incorporating experts' opinion and to determine the best green suppliers. Next, multi-objective linear programming is used to consider and to formulate various constraints such as quality control, capacity, and other objectives. The objective of the mathematical model is simultaneously to maximize the total value of purchasing and to minimize the total cost of purchasing. To handle the subjectivity of decision makers' preferences, fuzzy logic has been applied. The efficiency and application of the proposed approach has been illustrated with a case study in an automobile manufacturing company. The obtained results help firms establish a systematic approach for tackling green supplier selection and order allocation problems in a realistic situation. Finally managerial implications, conclusions, and directions for additional research are introduced. [Copyright &y& Elsevier]

Abstract: Cross-docking is considered as an efficient method to control the inventory flow, which is essential in supply chain management. In this paper, we consider a model that integrates cross-docking into the vehicle routing problem. In the model, a set of identical vehicles are used to transport goods from supplies to retailers through a cross-dock and the whole process must be completed in the planning horizon. Each supplier and retailer can be visited only once and the total quantity of goods in a vehicle must be less than its capacity. The objective of the problem is to determine the number of vehicles and a set of vehicle schedules with a minimum sum of operational cost and transportation cost. A new tabu search (TS) algorithm is proposed to obtain a good feasible solution for the problem. Through extensive computational experiments, it is shown that the proposed TS algorithm can achieve better performance than an existing TS algorithm while using much less computation time. The average improvements are as high as 10–36% for different size of problems. [Copyright &y& Elsevier]

Abstract: This paper considers advance order strategies in a two-echelon supply chain with one supplier and multiple buyers for seasonal products. We study how advance strategies affect the interactions between the supply chain members. In contrast to much of the literature, we specifically consider the supply chain with multiple buyers by introducing a demand function under uncertainty. Furthermore, we present two main different advance order strategies. We assume that exactly one of the multiple buyers has the ability to make an advance order before the selling season (we call this buyer the natural leader). In one strategy, the natural leader can only order products one time. The model shows that, below a threshold level of demand uncertainty, the supplier can benefit from providing adequate pricing incentives to entice the natural leader to order products before demand information is revealed. In another one, the natural leader can order products two times, we find that the supplier always can gain more profit from this advance order strategy. Our results show that the first advance order strategy is easier to control but has more strict constraint on coefficients of variation, while both two advance strategies bring more flexibility to the supply chain. [Copyright &y& Elsevier]

Discretionary models for evaluating the efficiency of suppliers assume that all criteria are discretionary, that is, controlled by the management of each supplier and varied at its discretion. These models do not assume supplier selection in the conditions that some factors are nondiscretionary. The objective of this paper is to propose a new pair of nondiscretionary factors-imprecise data envelopment analysis (NF-TDEA) models for selecting the best suppliers in the presence of nondiscretionary factors and imprecise data. A numerical example demonstrates the application of the proposed method. [ABSTRACT FROM AUTHOR]