Reverse Logistic Network Optimization Research for Sharing Bikes

With the fast development of sharing economy and network, sharing bikes increasingly become more and more popular. Sharing bikes are devoted to solving the problem in the last trip. In order to realize the maximization of benefit, companies always invest a large number sharing bikes to enhance the occupation ratio of market. However, they don't recovery the faulty bikes, thus causing traffic congestion and environmental pollution. This paper observes the cost of reverse logistic and customer satisfaction in significant regionals, then establishes a reverse logistic network for faulty sharing bikes. A Modified Genetic Simulated Annealing Algorithm(MGSA) is applied to solve this model. The computation results verify the effectiveness of the MGSA. (C) 2018 The Authors. Published by Elsevier Ltd.