Multiobjective Optimization for forward and Reverse Logistics Network Design in Rural Areas

Nowadays, we're all familiar with the speed of e-commerce development, but we have to admit that logistics industry in rural areas is still in its infancy. As deficient rural logistics network has restricted the rural development to a certain extent, this research field becomes a hot topic. However, most existing papers on forward and reverse logistics network design were primarily concerned with minimizing the total cost, neglecting the time sensitivity. In this paper, we propose a rural forward and reverse logistics network mode of e-commerce platform and a multiobjective mixed-integer linear programming model for logistics network design. To solve the NP-hard problem of the model, the nondominated sorting genetic algorithm II (NSGA-II) has been used. At last, the model has been used to design forward and reverse rural logistics network in Pinggu district of Beijing as an example, and the result show that the model is efficient for establishing virtuous rural logistics network.