基于改进遗传算法的连锁便利店配送路径优化

提出一种针对软时间窗下连锁便利店配送路径规划的带时间窗口的多染色体遗传算法。为解决单车场多车型带密集半软时间窗问题，讨论解决方案预防其陷入局部最优解。对于上述配送路径问题，提出多染色体改进遗传算法在减少车辆运输成本、惩罚成本的目标下进行最优路径求解，并为连锁便利店的路径规划案例提出车辆与路径选择的优化方案，最后将该算法与传统遗传算法进行实验对比分析。实验结果表明，本文算法在密集半软时间窗下，相比传统遗传算法明显减少了总配送成本，从而验证了本文算法的有效性。

Delivery route optimization of chain conveniencestores based on improved genetic algorithm

Based on the delivery route planning of chain convenience stores under soft time windows, a multi chromosome genetic algorithm with time windows for such scenarios is proposed to solve the problem of single distribution center with multiple types of vehicles under dense semi soft time windows, and its feasible solution of preventing falling into local optimal solution is discussed. For theabove mentioned delivery route planning problem, the proposed multi chromosome genetic algorithm solves the optimal route under the goal of reducing vehicle transportation cost and penalty cost, and proposes an optimization plan for vehicle and route selection for the chain convenience store's route planning case. Finally, the algorithm is compared with the traditional genetic algorithm. The experimental results show that this algorithm significantly reduces the total delivery cost in comparison to the traditional genetic algorithm under the dense semi soft time window, thus verifying the effectiveness of the algorithm.