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Accelerating Local Search in a Memetic Algorithm for the Capacitated Vehicle Routing Problem

机译:求解拥堵车辆路径问题的模因算法中的加速局部搜索

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Memetic algorithms usually employ long running times, since local search is performed every time a new solution is generated. Acceleration of a memetic algorithm requires focusing on local search, the most time-consuming component. This paper describes the application of two acceleration techniques to local search in a memetic algorithm: caching of values of objective function for neighbours and forbidding moves which could increase distance between solutions. Computational experiments indicate that in the capacitated vehicle routing problem the usage of these techniques is not really profitable, because of cache management overhead and implementation issues.
机译:模因算法通常需要较长的运行时间,因为每次生成新的解决方案时都会执行本地搜索。模因算法的加速需要专注于本地搜索,这是最耗时的组件。本文介绍了一种模因算法中两种加速技术在局部搜索中的应用:缓存邻居的目标函数值和禁止移动,这可能会增加解之间的距离。计算实验表明,在受限制的车辆路线选择问题中,由于缓存管理开销和实施问题,使用这些技术并没有真正的收益。

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