The Dynamic Design of Reverse Logistics Network with Fuzzy Incentive-Dependent Return
نویسندگان
چکیده
Reverse logistics (RLs) network design issues have been popularly discussed in recent years. However, few papers in past literature have been dedicated to the use of incentive effect on return quantity of used products. This study formulates an optimization model of RLs network design based on fuzzy mathematical programming with the aim of management in allocating used product by coordinating collection centers and recovery facilities to ensure minimum cost as well as maximum profit. In this model, fuzzy approach has been applied to interpret the relation between rate of product return and the incentives for each product return. This work assumes collection centers as having multi-capacity levels and the model is multi-period on which budget limit is considered. Finally, although this problem is known as NP-hard, for the sake of simplicity, a small numerical example is presented and solved in Lingo software to show the applicability of this model.
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