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Vehicle Routing Problem with Time Windows and Simultaneous Delivery and Pick-Up Service Based on MCPSO

机译：基于MCPSO的带时间窗和同时上门提货服务的车辆路径问题

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摘要

This paper considers two additional factors of the widely researched vehicle routing problem with time windows (VRPTW). The two factors, which are very common characteristics in realworld, are uncertain number of vehicles and simultaneous delivery and pick-up service. Using minimization of the total transport costs as the objective of the extension VRPTW, a mathematic model is constructed. To solve the problem, an efficient multiswarm cooperative particle swarm optimization (MCPSO) algorithm is applied. And a new encoding method is proposed for the extension VRPTW. Finally, comparing with genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, the MCPSO algorithm performs best for solving this problem.
机译：本文考虑了带有时间窗（VRPTW）的广泛研究的车辆路径问题的另外两个因素。这两个因素在现实世界中是非常普遍的特征，它们是不确定的车辆数量以及同时交付和接送服务。以总运输成本的最小化为扩展VRPTW的目标，构建了一个数学模型。为了解决该问题，应用了一种有效的多群协同粒子群优化算法。针对扩展VRPTW提出了一种新的编码方法。最后，与遗传算法（GA）和粒子群优化（PSO）算法相比，MCPSO算法在解决此问题方面表现最佳。

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  • 来源
    《Mathematical Problems in Engineering》 |2012年第8期|104279.1-104279.11|共11页
  • 作者

    Xiaobing Gan; Yan Wang; Shuhai Li; Ben Niu;

  • 作者单位

    College of Management, Shenzhen University, Shenzhen 518060, China;

    College of Management, Shenzhen University, Shenzhen 518060, China;

    College of Management, Shenzhen University, Shenzhen 518060, China;

    College of Management, Shenzhen University, Shenzhen 518060, China;

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