Growing environmental and economical concern has led to increasing attention towards management of product return flows. An effective and efficient reverse logistics network enables companies to gain more profit and customer satisfaction. Consequently, the reverse logistics network design problem has become a critical issue. After a brief introduction to the basic concepts of reverse logistics, the authors formulate a new integrated multi-stage, multi-period, multi-product reverse logistics model for a remanufacturing system where the inventory is considered. Two objectives, minimization of the costs and maximization of coverage, are addressed. Since such network design problems belong to a class of NP-hard problems, a multi-objective genetic algorithm and a multi-objective evolutionary strategy algorithm are developed in order to find the set of non-dominated solutions. Finally, the model is tested on test problems with different sizes, and the proposed algorithms are compared based on the number, quality, and distribution of non-dominated solutions that belong to the Pareto front.
Top1. Introduction
Reverse logistics can be defined as the process of moving goods and products from their usual destination to other locations and facilities in order to obtain value, or to manage safe disposal (Du & Evans, 2008). Environmental protection along with economic and service reasons has pushed a growing number of companies to consider product recovery and reverse flows within their logistics systems (Du & Evans, 2008; Lu & Bostel, 2007). Proper and effective implementation of reverse logistics can lead to savings in costs associated with inventory, transportation and waste disposal. It can also improve customer loyalty and future sales (Ko & Evans, 2007).
Product recovery options fall into different classes: refurbishing, cannibalization, repairing, recycling and remanufacturing (Thierry, Salomon, Van Nunen, & Van Waasenhove, 1995). Based on the condition and age of the returned product and economic considerations, the right option can be chosen (Guide, Jayaraman, Srivastava, & Benton, 2000). Common activities in product recovery systems can be grouped as follows (Aras & Aksen, 2008; Fleischmann, Krikke, Dekker, & Flapper, 2000):
Remanufacturing is known as the main option of recovery in terms of its feasibility and benefits (Lu & Bostel, 2007). It can return the used product to 'as new' condition through disassembly and inspection of all modules. Parts or modules that cannot be salvaged are replaced and tested. Sometimes it is even necessary to include technological upgrades. Remanufacturing is usually performed in-house by manufacturers, since they own the specific product knowledge (Beamon & Fernandes, 2004). Over the past decade, some firms such as Dell, General Motors, HP, Kodak and Xerox have focused on remanufacturing activities and carried out related operations successfully (Pishvaee, Kianfar, & Karimi, 2010a; Üster, Easwaran, Akçali & Çetinkaya, 2007).