多车场多目标开放式物流配送车辆调度问题的研究

Research for Multi-depot and Multi-objective Open-end Vehicle Scheduling in Distribution

为了优化现代物流中的车辆调度问题,文章针对多车场开放式物流配送车辆调度问题,建立了一种灵活的多目标组合优化模型,此模型可以方便地增减优化目标值;设计了适合多车场开放式车辆路径问题的通用染色体编码方案,并对遗传算法中的交叉变异操作做了详细说明,最终得到了多车场多目标开放式物流配送中车辆调度的优化策略;通过真实的测试用例验证了项目设计的优化模型和遗传算法在解决多车场多目标开放式物流配送车辆调度问题中的可行性。

In order to optimizing the vehicle scheduling of modern logistics,a flexible multi-objective optimizational model for open-end multi-depot vehicle scheduling is established,the model can conveniently increase or decrease the value of optimizational object.Using genetic algorithm a solving procedure and a chromosome coding methods without the restrictions of the optimum objective function is designed and made a detailed description for cross and mutation operation.The given test case verified the feasibility of the optimal model and genetic algorithm used in the multi-depot and multi-objective open-end vehicle scheduling in distribution.