Leveraging CPLEX to Solve the Vehicle Routing Problem with Time Windows

Van Manh Tran, T. Vu
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Abstract

In recent years, the problem of urban traffic has become increasingly urgent when the number of vehicles has increased rapidly while the transport infrastructure has not kept up with the increasing needs of passengers and drivers. Ridesharing or vehicle sharing are the optimal solutions to save travel time and cost and enhance convenience for passengers and vehicle drivers. The vehicle routing problem with time window (VRPTW), an expansion of Vehicle Routing Problem (VRP), has been examined in recent literature to find the most effective solutions to address the arrangement of customers with known requests while minimizing the cost on a given set of routes. This paper presents a model to address the vehicle routing problem with time windows (VRPTW) applying Mixed-Integer Programming (MIP) to optimize transportation costs and vehicles' numbers. The mathematical model of MIP was conducted in Java using the Branch and Cut algorithm and dynamic search algorithm in the IBM CPLEX library (cplex.jar). The model has been tested with two well-known cases of Solomon's benchmarking problem. The testing results demonstrate that both the cost and the number of vehicles are optimized reasonably with this model. Furthermore, sensitivity analysis for passenger nodes conducted on this model results indicates that the computation time and the number of vehicles increased when the number of customer nodes increased. This paper has widened several directions for future research to develop optimal solutions to vehicle sharing.
利用CPLEX求解带时间窗的车辆路径问题
近年来,随着车辆数量的迅速增加,而交通基础设施却跟不上乘客和司机日益增长的需求,城市交通问题变得越来越紧迫。拼车或车辆共享是节省出行时间和成本,增强乘客和车辆驾驶员便利性的最佳解决方案。带时间窗口的车辆路线问题(VRPTW)是车辆路线问题(VRP)的一个扩展,在最近的文献中,研究了在给定的一组路线上寻找最有效的解决方案,以解决具有已知请求的客户安排,同时最小化成本的问题。提出了一个基于混合整数规划(MIP)优化运输成本和车辆数量的带时间窗车辆路径问题模型。利用IBM CPLEX库(plex.jar)中的分切算法和动态搜索算法,在Java语言中建立了MIP的数学模型。这个模型已经用所罗门的基准问题的两个著名案例进行了检验。试验结果表明,该模型对成本和车辆数量都进行了合理的优化。此外,对该模型的乘客节点进行敏感性分析,结果表明,随着顾客节点数量的增加,计算时间和车辆数量增加。本文拓宽了未来研究的几个方向,以开发汽车共享的最优解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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