Abstract
Reverse logistics has acquired a boost because of various government legislation and several environmental, economic and social reasons. Different optimization approaches are widely applied in reverse logistics problems so as to attain different goals. Efficient production and transportation of the items improve the overall performance of the closed-loop supply chain networks. In this paper, we develop a multi-echelon and multi-item integrated production-transportation closed loop supply chain model. The model includes raw material suppliers, hybrid facilities, customers, collection centres, and disposal centres. Three objective functions under consideration are the minimization of total cost, total defected items and total delivery time. To deal with real life uncertainties we adopted the reliability approach for cost parameters whereas supply and demand parameters are considered as uncertain variables. Cost reliability parameters, as well as uncertain constraints are converted into their crisp equivalent form using necessary approaches. Fuzzy goal programming is used to obtain a compromise solution to the proposed model. The proposed model is tested on a real-life case study and finally, the results and conclusions are discussed. This paper provides acumen for fomenting the decision making process in logistics problems.
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