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Solving a Two-Stage Stochastic Capacitated Location-Allocation Problem with an Improved PSO in Emergency Logistics

机译：用改进的PSO解决紧急物流中的两阶段随机容量受限位置分配问题

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摘要

A stochastic expected value model and its deterministic conversion are developed to formulate a two-stage stochastic capacitated location-allocation (LA) problem in emergency logistics; that is, the number and capacities of supply centers are both decision variables. To solve thesemodels, an improved particle swarmoptimization algorithmwith the Gaussian cloud operator, the Restart strategy, and the adaptive parameter strategy is developed. The algorithm is integrated with the interior point method to solve the second-stage model. The numerical example proves the effectiveness and efficiency of the conversion method for the stochastic model and the proposed strategies that improve the algorithm.
机译：建立了随机期望值模型及其确定性转换模型，提出了应急物流中的两阶段随机容量限制位置分配问题。也就是说，供应中心的数量和能力都是决策变量。为了解决这些模型，开发了一种具有高斯云算子，重新启动策略和自适应参数策略的改进粒子群优化算法。该算法与内点法相集成以求解第二阶段模型。数值算例证明了该随机模型转换方法的有效性和有效性，并提出了改进算法的策略。

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  • 来源
    《Mathematical Problems in Engineering》 |2017年第6期|6710929.1-6710929.15|共15页
  • 作者

    Deng Ye; Zhu Wanhong; Tang Jian; Qin Jianfei;

  • 作者单位

    PLA Univ Sci & Technol, Coll Field Engn, Nanjing 210000, Jiangsu, Peoples R China;

    PLA Univ Sci & Technol, Coll Field Engn, Nanjing 210000, Jiangsu, Peoples R China;

    PLA Univ Sci & Technol, Coll Field Engn, Nanjing 210000, Jiangsu, Peoples R China;

    PLA Univ Sci & Technol, Coll Field Engn, Nanjing 210000, Jiangsu, Peoples R China;

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