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首页> 外文会议>2010 IEEE/ACS International Conference on Computer Systems and Applications >Exploiting grid computation for solving the Vehicle Routing Problem
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Exploiting grid computation for solving the Vehicle Routing Problem

机译：利用网格计算解决车辆路径问题

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The purpose of this paper is to solve the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) on Grid'5000 using the ParadisEO framework. In this respect, four packages developed in ParadisEO are exploited. First, EO package (Evolving Objects) is used to create an evolutionary algorithm to solve the mono-objective CVRPTW. Then, a related multi-objective problem is solved with MOEO package (Multi-Objective Evolving Objects). The package PEO (Parallel Evolving Objects) permitted us to use a particular hybridization scheme: the cooperative island model. Exchanges were performed between three evolutionary algorithms. With this strategy, an improvement in the solutions has been noticed. The final part of the work is concerned with developing hybridization between an evolutionary algorithm and a simulated annealing (created with the Moving Objects Package MO). The goal is to take advantage of intensification by simulated annealing and diversification by evolutionary algorithm. One important feature is the exploitation of the Grid'5000 infrastructure which permits us to reduce the execution time by 50 compared to a sequential execution.
机译：本文的目的是使用ParadisEO框架解决Grid'5000上带有时间窗（CVRPTW）的车辆停驶问题。在这方面，开发了ParadisEO开发的四个软件包。首先，使用EO程序包（演化对象）创建一种演化算法来解决单目标CVRPTW。然后，利用MOEO软件包（多目标演化对象）解决了一个相关的多目标问题。包PEO（并行演化对象）允许我们使用一种特殊的杂交方案：协作岛模型。三种进化算法之间进行了交换。通过这种策略，解决方案得到了改善。工作的最后一部分涉及开发进化算法和模拟退火（使用“移动物体包MO”创建）之间的杂交。目的是利用模拟退火的强化和进化算法的多样化。一个重要的功能是对Grid'5000基础结构的利用，与顺序执行相比，它使我们可以将执行时间减少50％。

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