A multiobjective dynamic rebalancing evolutionary algorithm for free-floating bike sharing

Abstract

The big challenge of free-floating bike sharing system is to rebalance the supply and demand in different places. Most studies are static rebalancing that moves bikes at night. Dynamic rebalancing considers the scheduling of transport vehicles during the day. It is more effective and difficult to solve. In this paper, a multiobjective dynamic rebalancing problem is solved. The two optimization objectives are considered: minimizing the total distance of rebalancing vehicle and minimizing the total demand unmet. A mathematic model is built to formulate the problem. A new algorithm SFMEA-AP (Sequence Flow Multiobjective Evolutionary Algorithm with Area Protected) that uses the sequence flow encoding is proposed. An novel area protected strategy that includes a non-dominated sorting with similarity comparison is proposed. It simultaneously considers the fairness and competitiveness in solution space. Six neighborhood search operators are designed. They are used as variable neighborhood search strategy. Computational experiments show that SFMEA-AP can obtain better solution quality than SFMEA-VNS, QMOEA, NSGA-II, ILS and LSMOVRPTW. The IGD values of non-dominated solutions of SFMEA-AP are better than those of SFMEA-VNS, QMOEA, NSGA-II, ILS and LSMOVRPTW. In addition, the non-dominated solution set of SFMEA-AP have good diversity.