An Inverse Optimization Approach of Vehicle Routing Problem

Abstract

Generally, experienced drivers or experts do not always follow the shortest path in the last mile delivery of e-commerce. Hence, an inverse optimization approach was proposed to obtain a proper cost matrix by learning from the experts’ past experience. Thus, the routing model with respect to the learned cost matrix could provide solutions as good as those given by experts. An algorithm-based multiplicative weights updates algorithm was applied to achieve the experience learning process. The experimental analyses based on the random and real-life instances demonstrate the effectiveness of this approach.

Keywords

• inverse optimization
• vehicle routing problem(vrp)
• cost matrix
• experience learning