Bike-sharing rebalancing problem

Abstract

The number of bike-sharing services has rapidly increased in many cities worldwide. One of the main challenges of the bike-sharing system operation costs is allocating enough bikes and parking space. This paper presents a model for solving the bike-sharing relocation problem. The artificial bee colony (ABC) algorithm is an efficient approach, but it is still insufficient for the selection strategy. ABC has been adopted in various problems to improve the performance of various systems. This research proposed a modified ABC algorithm in a neighbor solution to enhance the solution performance, namely guided local search (GLS), to apply to the design route for transportation while truck relocation bikes each station in the bike-sharing system. Computational experiments were performed to find out the best modeling solution in the case. The implementations were experimental for the same data instances, which made it possible to compare the performance algorithms so as to solve the bike-sharing relocation problem of the pickup and drop off. The results showed that the GLS-ABC method can be a better solution than the original one. The statistically significant p-value of the mean objective value of the different algorithms was smaller than 0.05. Thus, the impact of minimizing the route tour cost in solving the bike-sharing relocation problem.