摘要
在中国,大部分物流公司调度车辆运输医疗器械的水平不高,存在着路径重复或是装配重量不合理的问题,上述问题导致车辆总路程变长,引发严重的资源浪费和环境污染。文章提出一种遗传算法用于解决上述问题。首先将问题抽象并建立数学模型,结合现实情况和车辆路径规划问题,针对医疗器械运输场景提出特定约束与路径优化策略,然后根据约束条件重点进行可行解设计、选择策略、交叉策略和变异策略,并展开详细的说明。最后通过C语言生成了两个小规模算例来验证算法的各方面性能。实验结果表明,该遗传算法在解决小规模算例时收敛速度快,解的质量高,稳定性较强,可以在满足各医院不同需求的条件下,使车辆行驶路径最短。
ed and a mathematical model is established.Based on the actual situation and the vehicle routing problem,specific constraints and path optimization strategies are proposed for the medical device transportation scenario.Then,the design of feasible solutions,selection strategy,crossover strategy,and mutation strategy are developed based on these constraints,and detailed explanations are provided.Finally,two small-scale cases are generated using the C programming language to evaluate the algorithm's performance.The experimental results demonstrate that the proposed genetic algorithm achieves fast convergence,high solution quality,and good stability in solving small-scale cases.It effectively minimizes vehicle travel distance while satisfying the varying demands of different hospitals.
作者
赵振然
田亮
蒲靖涛
ZHAO Zhenran;TIAN Liang;PU Jingtao(School of Automotive,Chang'an University,Xi'an 710018,China;Sichuan Chengnan Expressway Co.,Ltd.,Chengdu 610051,China)
出处
《物流科技》
2026年第2期111-115,共5页
Logistics Sci Tech
基金
四川省交通科技项目(2021-ZL-02)。
关键词
车辆路径规划
遗传算法
可行解设计
选择策略
交叉策略
vehicle routing problem
genetic algorithm
feasible solution design
selection strategy
crossover strategy
