混合遗传算法求解双目标带时间窗的车辆调度问题

Bi-objective Vehicle Scheduling Problem with Time Window Using Hybrid Genetic Algorithm

作为物流配送的关键一环,车辆调度问题是运输环节优化的核心问题之一.企业要想提高自身经济效益,降低成本,实现高额利润就必须要采用先进的车辆调度方案.先进的车辆调度方案既需要降低购买车辆的固定投入,又需要减少车辆总行驶路径消耗的有形成本,还需要提高客户满意度以此维系与老客户的关系来降低无形的成本.为此,本文研究建立以配送车辆数最少和总行驶距离最短的双目标带时间窗的车辆调度模型,并在遗传算法中融入两元素优化算法设计新的混合遗传算法来求解该模型,为企业提供决策支持.通过对实例的求解证明,所建模型和设计的算法均具有有效性和合理性.

As a critical party of logistics distribution,vehicle scheduling is a core issue of transportation optimization.To improve economic benefits,reduce costs and obtain high profits,enterprises should adopt advanced vehicle scheduling solutions.An advanced vehicle scheduling solution is able to reduce the fixed investment such as vehicle purchase,the tangible cost related to the total driving distance,and the intangible cost spent on enhancing customer satisfaction to maintain the relationship with regular customers.In this paper,a bi-objective vehicle scheduling model with time window is established for the two objectives of least distribution vehicle number and minimum total driving distance,and a novel hybrid genetic algorithm is designed to solve the model by integrating the bi-objective optimization algorithm into the genetic algorithm,which will provide decision support for enterprises.The validity and rationality of the model and the algorithm are proved by examples.