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A fleet size and mix vehicle routing problem with quantity discounts for outsourcing

机译:车队规模和混合车辆路径问题以及外包的数量折扣

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In view of the fleet size and mix vehicle routing problem with quantity discounts for outsourcing, a non-linear programming model is established; and an evolutionary algorithm based on the shortest path encoding approach is designed to solve the model by minimize the variable costs and outsourcing costs. Through experimental analysis, it is shown that: the mutation probability and population size affects the optimal fitness defined by total costs; the higher mutation probability and bigger population size would quicken the convergence speed and quality of the evolutionary algorithm; the bigger population size would cost more computational time; other parameters impose no significant effect on experimental results. Based on these results, optimal parameters for the algorithm are determined. By a case, the performance and the effects of the algorithm are demonstrated.
机译:针对车队规模和混合车辆路径问题以及外包数量折扣问题,建立了非线性规划模型。设计了一种基于最短路径编码的进化算法,通过最小化可变成本和外包成本来求解模型。通过实验分析表明:突变概率和种群规模影响总成本确定的最优适应度;较高的变异概率和较大的种群规模将加快进化算法的收敛速度和质量。更大的人口规模将花费更多的计算时间;其他参数对实验结果没有明显影响。根据这些结果,确定算法的最佳参数。通过实例说明了该算法的性能和效果。

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