Reverse logistics network design for automotive glass recycling

End-of-life vehicles (ELVs), as an important renewable resource, have huge environmental and economic benefits. Since closed-loop and reverse logistics network make an infrastructure to collect and recover used products, developing an effective reverse logistics network as a major greening tool in automotive supply chains has been growing increasingly by researchers. Car consists of many parts and materials that are different together. So that the reverse logistics should be design individually for each. With attention to the automotive glass represents approximately 3% (by mass) of the total composition of a car, its recycling have significant benefit comparing to use virgin material. In this research, a profit model multi-echelon reverse logistics network including collection center, shredder center and recycling center is developed to recycle automotive glass. Concerning the complexity of the reverse logistics network, traditional method cannot be implemented for solving them. Then, an evolutionary algorithm based genetic algorithm (GA) is applied as a solution methodology to solve mixed integer linear programming model on a numerical example and find the optimum solution.