采用改进遗传算法的城市垃圾车辆调度研究  

Research on urban garbage vehicle scheduling using improved genetic algorithm

作　　者：雷筱珍[1] LEI Xiao-zhen(College of Innovation and Entrepreneurship,Fujian Chuanzheng Communications College,Fuzhou,Fujian 350007,China)

机构地区：[1]福建船政交通职业学院创新创业学院,福建福州350007

出　　处：《宁德师范学院学报(自然科学版)》2024年第4期381-387,共7页Journal of Ningde Normal University(Natural Science)

摘　　要：为解决城市垃圾运输车辆调度运营费用普遍过多问题,提出一种多约束运输车辆调度优化算法。考虑垃圾分类运输公司车辆数量、车辆限载、调度车辆数量等约束,建立垃圾运输调度优化模型。依据垃圾量和车辆限载量,确定最小运输车辆数,选自然数为染色体编码初始化群体,引入动态自适应变异算子,利用多段非线性调整方法进行变异操作,通过迭代获得车辆最优调度方案。实验结果表明:改进后的算法可获得较优的运输调度方案,行驶距离明显短于传统遗传算法,可有效应用于城市垃圾运输车辆调度问题的求解。In order to solve the problem of excessive operating expenses in the scheduling of urban garbage transportation vehicles,a multi-constraint transportation vehicle scheduling optimization algorithm was pro⁃posed.Considering the constraints of the number of vehicles,the vehicle load limit,and the number of dispatch⁃ing vehicles of the garbage sorting and transportation company,an optimization model of garbage transportation scheduling was established.According to the amount of garbage and the vehicle load limit,the minimum num⁃ber of transport vehicles is determined.The natural number is selected as the chromosome coding initialization population,a dynamic adaptive mutation operator is introduced,and a multi-segment nonlinear adjustment method is used to carry out the mutation operation.The optimal vehicle scheduling scheme is obtained through iteration.The experimental results show that the enhanced algorithm can obtain a better transportation schedul⁃ing scheme,and the driving distance is significantly reduecd in comparison to the conventional genetic algo⁃rithm,which can effectively solve the scheduling problems associted with urban garbage transportation vehicles.

关 键 词：垃圾运输车 车辆调度 路径规划 遗传算法 染色体交叉算法 自适应变异算子 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]