An improved crossover particle swarm optimization algorithm for automatic order sorting in distribution center

Yuze Xu, Linxuan Zhang, Hui Li, M. Ge, Wanyi He
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Abstract

In this paper, the automatic order sorting problem with scattered storage is studied. First, the mathematical model of the problem is established. Then an improved crossover particle swarm optimization (CPSO) algorithm is proposed for order batching, batch sequencing and storage selection. The CPSO mainly conducts the position update of particle swarm optimization algorithm by using crossover, which makes it more suitable for discrete problems. In order to enhance the local search capability of the algorithm, a variable neighborhood search (VNS) algorithm is proposed. And the neighborhood structure of the automatic order sorting problem for scattered storage is defined. The VNS will further search the neighborhood of the global optimal solution after each operation of the CPSO position update. Finally, the effectiveness of the proposed CPSO is verified by numerical experiments.
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配送中心自动排序的改进交叉粒子群算法
本文研究了具有分散存储的自动排序问题。首先,建立了问题的数学模型。然后提出了一种改进的交叉粒子群算法(CPSO),用于批量订货、批量排序和存储选择。CPSO主要通过交叉对粒子群优化算法进行位置更新,使其更适合于离散问题。为了提高算法的局部搜索能力,提出了一种可变邻域搜索(VNS)算法。定义了离散存储自动排序问题的邻域结构。在每次CPSO位置更新操作后,VNS将进一步搜索全局最优解的邻域。最后,通过数值实验验证了该算法的有效性。
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