Abstract
A network design of a closed-loop supply chain (CLSC) with multiple recovery modes under fuzzy environments is studied in this article, in which all the cost coefficients (e.g., for facility establishment, transportation, manufacturing and recovery), customer demands, delivery time, recovery rates and some other factors that cannot be precisely estimated while designing are modeled as triangular fuzzy numbers. To handle these uncertain factors and achieve a compromise between the two conflicting objectives of maximizing company profit and improving customer satisfaction, a fuzzy bi-objective programming model and a corresponding two-stage fuzzy interactive solution method are presented. Applying the fuzzy expected value operator and fuzzy ranking method, the fuzzy model is transformed into a deterministic counterpart. Subsequently, Pareto optimal solutions are determined by employing the fuzzy interactive solution method to deal with the conflicting objectives. Numerical experiments address the efficiency of the proposed model and its solution approach. Furthermore, by comparing these results with the CLSC network design in deterministic environments, the benefits of modeling the CLSC network design problem with fuzzy information are highlighted.
Highlights
In recent years, the closed-loop supply chain (CLSC) has attracted attention for its economic value, environmental impacts and governmental attention in the area of supply chain management
Through the TH evaluation function, we find that a trade-off between the weighted and the minimum operators can be achieved, the decision-makers can adjust the parameters wg and γ to obtain equilibrium and non-equilibrium solutions between the two objectives according to their preferences
This paper studies the network design problem of the CLSC with multiple recovery models by putting it under fuzzy environments and establishing a fuzzy bi-objective mixed linear programming model, wherein the objectives of maximizing enterprise’s profit and maximizing service level measured by delayed delivery time are taken into consideration
Summary
The closed-loop supply chain (CLSC) has attracted attention for its economic value, environmental impacts and governmental attention in the area of supply chain management. This paper differentiates itself from the existing related research and contributes to the study of the CLSC network design from the following aspects: (1) considering the most comprehensive recovery options simultaneously, as compared to the other works in Table 1; (2) establishing a fuzzy bi-objective MILP model which maximizes both company profit and customer satisfaction level for the CLSC network design under fuzzy environments; (3) presenting a two-stage fuzzy interactive solution framework to solve the formulated fuzzy optimization model by integrating the fuzzy expected value operator, fuzzy ranking method and fuzzy interactive solution method; (4) comparing the performance of the fuzzy CLSC model with the deterministic one in [3] by several numerical experiments to demonstrate the importance and necessity of designing the CLSC network under fuzzy environments.
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