A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return

A closed-loop supply chain (CLSC) network consists of both forward and reverse supply chains. In this paper, a CLSC network is investigated which includes multiple plants, collection centres, demand markets, and products. To this aim, a mixed-integer linear programming model is proposed that minimizes the total cost. Besides, two test problems are examined. The model is extended to consider environmental factors by weighed sums and ε-constraint methods. In addition, we investigate the impact of demand and return uncertainties on the network configuration by stochastic programming (scenario-based). Computational results show that the model can handle demand and return uncertainties, simultaneously

A Web Based Optimization System Using Goal Programming for Supply Chain Network

Considering high competitive nature of todays industries,being on plan is very vital for supply chain network of an organization. Allthe flows of materials from initial suppliers to final customers need to besmooth. Hence, distribution network design is an important strategic decisionproblem for the supply chain managers. The aim of this research is to propose a web-based Decision Support System (DSS) foroptimizing fuzzy distribution network in the context of supply-chain management. A fuzzy goal-programming model has been designedfor the proposed DSS to consider the uncertain and imprecise data. Thisresearch focuses on four conflict fuzzy goals of (i). all demands must be covered by distribution center, (ii).investment goals for opening new sites considering fix costs, (iii). Investmentgoals for opening new distribution centers considering fix costs, (iv). Supplycosts goals, to meet the optimized results. Hence with those attributes ofmembership function of goals, the decision makers can apply this model toobtain the investment policy and the achieved level of each individual goal

A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills the gap between theories of inter-organizational relationships and quantitative models. Thus, a novel Robust Fuzzy Possibilistic AHP approach is proposed for combining the benefits of two complementary theories of inter-organizational relationships named, (1) Resource-based view, and (2) Transaction-cost theory and considering Fit theory as the perquisite of alliance success. The Robust Fuzzy Possibilistic AHP approach is a noveldevelopment of Interval-AHP technique employing robust formulation; aimed at handling the ambiguity of the problem and let the use of intervals as pairwise judgments. The proposed approach was compared with existing approaches, and the results show that it provides the best quality solutions in terms of minimum error degree. Moreover, the framework implemented in a case study and its applicability were discussed

An Experimental Research on Closed Loop Supply Chain Management with Internet of Things

Abstract. Closed loop supply chain (CLSC) optimization is integration of forward and reverse logistics activities. The importance of CLSC management is increasing by legal regulations, limited energy resources and environmental- financial problems that growing in recent years. However, reverse logistics part of the CLSC is a flow type which is more difficult to made predictions, planning and controls by reason contained uncertainties. This stage, Internet of Things system reduces related uncertainties by providing all the life information of the returned product and substantially attenuates planning of reverse flow activities. In this study, a CLSC is considered that meets demands of the sales&collection center both new and remanufactured product. Manufacturer has three options (refurbishing, disassembly and disposal) to assessing returned products. A mixed integer linear programming model is proposed for a single type of product is completely modular (automobile, computer, telephone, etc.). The model meets customer's products and components demands based period, maximizes profit consist of different sales revenues and total cost (total production, purchase, transportation and disposal costs) and determines how to evaluate all returned products. The proposed model has been verified with the aid of a numerical example by solving in GAMS software and its performance reviewed with experimental studies.Keywords. Closed loop supply chain optimization, Internet of Things, Mixedinteger linear programming, Returned product management.JEL. L80, L86, Q55