Multiobjective Reverse Logistics Model Considering Inventory Systems with Backordering

Today, interests about the recovery of used products and materials are increasing. Therefore, Reverse Logistics will become power and great potential for winning consumers in more competitive marketing surroundings in the future. The reverse logistics is the process flow of used-products that are collected to be reproduced so that they can be sold again to customers after some processing. This research is to develop and solve a model for just-in-time (JIT) distribution in the context of reverse logistics. A multiobjective model is two-echelon reverse logistics, with two objective functions: minimizing cost of reverse logistics model (i.e. transportation cost, disposal cost, purchase cost and inventory holding cost), and just-in-time delivery to minimize the costs of backorders and inventories with relationship between the demands of products and the quantity of provided products from processing center, capacity constraints are also considered in a multi-period network. In the experimental results comparing CPLEX(mathematical solver manufactured by ILOG Inc.) and pri-awGA (priority-based adaptive weight Genetic Algorithm), we demonstrated the effectiveness of pri-awGA such as shortness of computational time and better solutions.