Sustainable Inventory Routing Problem for Perishable Products by Considering Reverse Logistic

Abstract : Managing the expiration date of perishable products, gathering the expired products, pollution and cost of recycling the expired products and etc. brings complexity in considering the perishable products in Inventory/Routing Problem (IRP). Moreover, taking into account other criteria such as environmental criteria, social criteria, fuel consumption, respecting time windows and etc. apply more complexity in the IRPs. On the other hand, increase of pollution and pressure of social communities force the managers to pay attention to environmental and social issues. This paper proposes a new bi-objective mathematical model concerning economic, social and environmental issues in distribution of perishable products with specified expiration date in IRPs. First objective focuses on traditional costs of inventory and distribution as well as age and price strategy. Second objective function concerns in maximization of social issues calculated by considering rate of vehicle accident as well as number of expired products. Moreoer. in order to reduction complexity of proposed model, vehicle noise emission as another social issue as well as some environmental criteria have been taken into account as constraint. Since, expired products have direct effect in environmental side and should be recycled, concept of reverse logistic is also applied for gathering the expired products from retailer and return back to supplier. In order to solve the model and reach compromise solution the Torabi-Hassini method is applied. Finally sensitivity analysis is performed to investigate effects of variation of social issues in economic side of proposed problem. (C) 2016, IFAC(International Federation of Automatic Control) Hosting by Elsevier Ltd. All right reserved.
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Mohammad Rahimi, Armand Baboli, Yacine Rekik. Sustainable Inventory Routing Problem for Perishable Products by Considering Reverse Logistic. 8th IFAC Conference on Manufacturing Modelling, Management and Control (MIM 2016), Jun 2016, Troyes, France. pp.949--954, ⟨10.1016/j.ifacol.2016.07.898⟩. ⟨hal-01575877⟩



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