基于遗传算法的航空物流配送路径优化分析  

Genetic Algorithm-Based Air Logistics Distribution Path Optimization Analysis

作　　者：杨晓康[1] 宋秀峰 YANG Xiaokang;SONG Xiufeng(Department of International Transportation and Logistics,Shandong Vocational College of Foreign Trade,Qingdao 266100,China;Qingdao Geer Acoustics Technology Co.,Ltd.,Qingdao 266041,China)

机构地区：[1]山东外贸职业学院国际运输与物流系民航教研室,山东青岛266100 [2]青岛歌尔声学科技有限公司,山东青岛266041

出　　处：《自动化仪表》2022年第12期109-112,共4页Process Automation Instrumentation

摘　　要：为降低航空物流运输成本,提高航空物流运输能力、航空货运量和货运服务质量,在传统遗传算法的基础上,建立航空物流配送路径优化模型。对问题进行格雷码编码处理和遗传算法的交叉、变异操作。为提升算法的搜索精度和收敛速度,提出一种自适应变异方法来提升种群的多样性。引入模拟退火算法的Metropolis准则,提升路径规划效率,实现全局的最优化路径目标寻找。将改进算法应用于航空多枢纽物流路径规划,很好地解决了航空物流配送中的运输路径优化和站点求解问题,且算法的收敛速度和收敛精度有显著提高。后期可引入航空物流配送中经济成本、服务质量、路径选择等参数来建立路径的优化模型,实现服务质量、运输成本的双控目标。To reduce the cost of air transport logistics transportation,improve the needle air logistics transportation capacity,air cargo volume and cargo service quality,on the basis of traditional genetic algorithm,the optimization model of air logistics distribution path is established.The problem is processed by Gray code coding and crossover and variation operation with genetic algorithm.To improve the search accuracy and convergence speed of the algorithm,an adaptive mutation method is proposed to enhance the diversity of the population.The Metropolis criterion of the simulated annealing algorithm is introduced to improve the efficiency of path planning and to achieve global optimal path objective finding.The improved algorithm is applied to air path multi-hub logistics path planning,which well solves the transport path optimization and station solving problems in air logistics distribution,and the convergence speed and convergence accuracy of the algorithm are significantly improved.In the later stage,parameters such as economic cost,service quality and path selection in air logistics distribution can be introduced to establish the optimization model of paths and achieve the dual control objectives of service quality and transportation cost.

关 键 词：航空运输 遗传算法 交叉 变异 适应度 退火算法 最优路径 运输成本 

分 类 号：TH166[机械工程—机械制造及自动化]