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M-NSGA-II: A Memetic Algorithm for Vehicle Routing Problem with Route Balancing

机译:M-NSGA-II:具有路径平衡的车辆路径问题的模因算法

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The vehicle routing problem with route balancing (VRPRB) is a variant of classical VRPs. It is a bi-objective optimization problem which considers the total length of routes and the balance issue among different routes. In this paper, the balance objective we introduce is the minimization of the maximal route length, which can effectively avoid the occurrence of distorted solutions. We develop an NSGA-II based memetic algorithm (M-NSGA-II) for the VRPRB. The M-NSGA-II algorithm combines the NSGA-II algorithm with a local search procedure which consists of four local search operators. To evaluate our algorithm, we test it on the standard benchmarks and compare our results with the referenced approach. Moreover, we analyze the effect of different local search operators on M-NSGA-II algorithm. Computational results indicate that our M-NSGA-II algorithm is able to produce better solutions.
机译:具有路线平衡(VRPRB)的车辆路线问题是经典VRP的一种变体。它是一个双目标优化问题,它考虑了路径的总长度以及不同路径之间的平衡问题。在本文中,我们引入的平衡目标是最大路径长度的最小化,这可以有效避免扭曲解的出现。我们为VRPRB开发了基于NSGA-II的模因算法(M-NSGA-II)。 M-NSGA-II算法将NSGA-II算法与包含四个本地搜索运算符的本地搜索过程结合在一起。为了评估我们的算法,我们在标准基准上对其进行了测试,并将我们的结果与参考方法进行了比较。此外,我们分析了不同的本地搜索运算符对M-NSGA-II算法的影响。计算结果表明,我们的M-NSGA-II算法能够提供更好的解决方案。

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