Can I read A Multiobjective Evolutionary Algorithm with Variable Neighborhood Search for the Dynamic Rebalancing of a Bike-sharing System on EtoBox?

A Multiobjective Evolutionary Algorithm with Variable Neighborhood Search for the Dynamic Rebalancing of a Bike-sharing System by Sheng Su; Dongwen Xiong; Haijie Yu is a scholarly article available to read on EtoBox.

What is A Multiobjective Evolutionary Algorithm with Variable Neighborhood Search for the Dynamic Rebalancing of a Bike-sharing System about?

Dynamic rebalancing is a key operation to free-floating bike sharing system. It can solve the imbalance of bike supply in different locations during the daytime. It is more meaningful and more difficult to solve than static rebalancing. In this paper, a multiobjective dynamic rebalancing problem minimizing the total distance of rebalancing vehicle and the total demand unmet is considered. A mathematic model is built to formulate the problem. A sequence flow multiobjective evolutionary algorithm with variable neighborhood search SFMEA-VNS is proposed. A sequence flow encoding and non-dominated sorting with similarity comparison are developed. Seven neighborhood search operators are designed and applied in the algorithm. Computational experiments show that SFMEA-VNS can obtain better solution quality than NSGA-II, SPEA2, ILS and LSMOVRPTW. The non-dominated solution of SFMEA-VNS can dominate all non-dominated solutions obtained by NSGA-II, SPEA2, ILS and LSMOVRPTW. In addition, the non-dominated solution set of SFMEA-VNS has good diversity.

Author

Sheng Su; Dongwen Xiong; Haijie Yu

Publisher

ACM

Published

2022

Language

EN