贪心免疫优化算法求解带时间窗的冷链物流选址路径问题  

Research on Greedy Immune Optimization Algorithm for Solving the Problem of Cold Chain Logistics Location Path with Time Windows

作　　者：宁雅敬 张惠珍[1] NING Yajing;ZHANG Huizhen(School of Management,Shanghai University of Science and Technology,Shanghai 200082,China)

机构地区：[1]上海理工大学管理学院,上海200082

出　　处：《物流科技》2024年第8期140-146,共7页Logistics Sci-Tech

摘　　要：文章针对冷链物流选址路径问题,提出了一种贪心免疫优化算法。首先,建立了考虑物流时间窗约束的选址路径模型,以最小化选址成本、车辆启用成本和运输成本为目标。其次,设计了贪心免疫优化算法来解决该问题。该算法使用六层抗体编码方法,有效提高了抗体突变控制精度和抗体解码效率。通过对初始抗体群体进行贪心预优化,在不压缩丢失抗体突变空间的前提下,提高了初始抗体的适应性。通过对抗体突变方向权值的自适应迭代,提高了算法的优化效率。数值分析结果表明,提出的算法在有时间窗的定位路径问题中具有较好的优化能力,构建的模型可以有效降低定位路径问题的总成本。This paper proposes a greedy immune optimization algorithm for cold chain logistics location and routing problems.Firstly,the paper establishes a location path model that considers logistics time window constraints,with the goal of minimizing location costs,vehicle activation costs,and transportation costs.Secondly,the paper designs a greedy immune optimization algorithm to solve this problem.This algorithm uses a six layer antibody encoding method,effectively improving the accuracy of antibody mutation control and antibody decoding efficiency.By performing greedy pre optimization on the initial antibody population,the adaptability of the initial antibody is improved without compressing the loss of antibody mutation space.The optimization efficiency of the algorithm has been improved through adaptive iteration of antibody mutation direction weights.The numerical analysis results indicate that the proposed algorithm has good optimization ability in location path problems with time windows,and the constructed model can effectively reduce the total cost of location path problems.

关 键 词：选址路径 时间窗 贪心免疫优化 

分 类 号：F252[经济管理—国民经济] U116[交通运输工程]