重庆大学学报2013，Vol.36Issue(8)：40-46,7.DOI:10.11835/j.jssn.1000-582X.2013.08.007
云自适应遗传算法有能力约束的车辆调度优化
Research on capacitated vehicle routing problem with cloud adaptive genetic algorithm
摘要
Abstract
Aiming at traffic volume and vehicle utilization,which are closely related to the cost of vehicle traffic,a vehicle scheduling model with the minimum fuel cost and fixed cost is established.According to the requirement of real-time and complicacy of the vehicle scheduling,a cloud adaptive genetic algorithm is proposed by combining cloud model theory with genetic algorithm.The way of the fixed set crossover and mutation probability in the standard genetic algorithm is improved by using the randomness and bias stability of the cloud droplet cloud model.Defects of slow search and easy precocious of the standard genetic algorithm is overcome.The convergence and robustness of the algorithm was improved by crossover and mutation that was designed based on maximum retention mechanism.Finally,an example authenticated the effectiveness of the model and algorithm.关键词
车辆调度问题/标准遗传算法/云遗传算法/云模型Key words
vehicle routing problem/ standard genetic algorithm/ cloud genetic algorithm/ cloud model分类
管理科学引用本文复制引用
蹇洁,王旭,葛显龙..云自适应遗传算法有能力约束的车辆调度优化[J].重庆大学学报,2013,36(8):40-46,7.基金项目
重庆市决策咨询与管理创新计划资助项目(CSTC2013JCCXA0109) （CSTC2013JCCXA0109）
工业与信息化部软科学资助项目(2013-R-10-2) （2013-R-10-2）
重庆邮电大学社会科学基金资助项目(K2012-95) （K2012-95）
国家社会科学基金资助项目(11BGL006) （11BGL006）
