基于混合遗传算法的应急物资配送路径优化

为解决突发事件下应急物资的配送路径优化问题,以配送车辆的固定成本、运输成本、违反最大载重量以及右时间窗的惩罚成本之和最小为目标,构建了带时间窗约束的应急物资配送路径优化模型;通过将遗传算法与节约算法、大规模邻域搜索算法相结合,设计出了一种混合遗传算法对模型进行求解;最后用算例仿真验证了模型和算法的可行性。实验结果表明:设计的混合遗传算法在求解过程和求解结果上都比标准遗传算法更优,可见能够为解决应急物资的配送路径优化问题提供科学的决策依据。

Optimization of Emergency Material Distribution Path Based on Hybrid Genetic Algorithm

In order to solve the problem of emergency material distribution path optimization under emergencies, an optimization model of emergency material distribution path with time window constraint was constructed, which aimed at minimizing the sum of fixed cost, transportation cost, penalty cost of violating the maximum load capacity and right time window. And a hybrid genetic algorithm was designed to solve the model by combining genetic algorithm with saving algorithm and large-scale neighborhood search algorithm. Finally, an example was given to verify the feasibility of the model and algorithm. The experimental results show that: the hybrid genetic algorithm is better than the genetic algorithm in the solution process and results, which can provide scientific decision-making basis for solving the emergency material distribution path optimization problem.