细菌觅食优化算法求解物流配送问题

Bacterial Foraging Optimization Algorithm for Solving Problem of Fresh Logistics Distribution

针对物流配送问题,在综合考虑时间、成本两个影响因素的前提下,提出一种针对离散多目标选址-路径问题(LRP)的改进细菌觅食优化算法。该算法通过构建相应的带软时间窗选址-路径问题模型,并根据Pareto支配关系对标准细菌觅食优化算法(BFOA)进行了改进,此外,在个体互不支配的时候,采用归一化方法进行择优处理,通过引入惩罚函数来约束车辆所负责的客户需求不超过其载重限制。设计的相应多目标细菌觅食优化算法(MOBFO)对物流配送问题进行了求解,并通过使用CVRP库中的算例,对算法的有效性和优劣性也进行了验证,对于LRP模型问题提供了一定的参考。实验结果表明,设计的多目标细菌觅食优化算法在求解物流配送问题上具有一定的优越性,同时对于多个目标的优化问题也具有一定的优势。

Aiming at the problem of fresh logistics distribution,on the premise of synthetically considering both time and cost,we propose an improved bacterial foraging optimization algorithm for location routing problem(LRP).This algorithm improves the standard bacterial foraging optimization algorithm(BFOA)by establishing the corresponding model with soft time window addressing-path problem on the basis of Pareto dominant relationship.In addition,when the individuals don’t dominate each other,the normalized method is adopted to select the best,and the penalty function is introduced to restrict the customer demand of vehicle to not exceed its load limit.The corresponding multi-objective bacterial foraging optimization algorithm(MOBFOA)is designed to solve the problem of logistics distribution,and its effectiveness and advantages and disadvantages are also validated by using the examples of the CVRP library,which provides a certain reference for the LRP model problem.The experiment shows that the proposed algorithm had certain priority in solving logistics distribution problems and also certain advantages in the optimization of multiple objectives.