基于粒子群算法的共享单车站间调度优化方法

对单车实行精准高效的调度是目前共享单车系统亟须攻克的重要难题之一。共享单车的调度问题可以看作是一个受时间、地域、人流等多因素影响的NP完全问题(Non-deterministic Polynomial Complete Problem)。目前,我国在这一方面的研究工作尚不成熟。根据单车调度实际情况,考虑调度车容量与站点满意度约束,以旅行商问题为基础,建立综合优化最大化的共享单车站间调度数学模型,通过优化多目标问题的混合禁忌-粒子群算法,对上述模型进行求解。最后以合肥市大学城实际单车站点为算例,以该算法进行求解。结果证实该算法可以得到综合最优的调度路线。

On Solutions to the Problem of Scheduling Shared Bicycles between Sites Based on Particle Swarm OptimizationAlgorithm

Accurate and efficient scheduling of shared bicycles is one of the key problems to be solved. This problem can be regarded as a Non-deterministic Polynomial Complete Problem affected by time, place, population and other factors. Currently, study on this problem is still far from mature in our country. Regarding actual bicycle scheduling, considering the constraints of scheduling capacity and site satisfaction, and based on the Travelling Salesman Problem, a comprehensively and maximally optimized mathematical model of scheduling shared bicycles between sites is provided. Then, Tabu Search-Particle Swarm Optimization (TS-PSO) algorithm of multi-objective problem is adopted to solve the above model. Finally, this algorithm is used to solve the practical problem. The results show that a comprehensively optimal scheduling route can be achieved through the algorithm.