摘要
针对金融押运成本高且各押运线路工作量不均衡等问题,提出一个综合优化目标和解决方案,建立以押运成本最优化和押运线路工作量均衡为目标的多目标优化模型.选取上海保安押运有限公司在青浦区的早送晚接业务数据建立实际算例,以Solomon插入节约算法获取初始解,并采用基于模拟退火算法的LocalSolver和带精英保留策略的非支配排序遗传算法(non-dominated sorting genetic algorithm-Ⅱ,NSGA-Ⅱ)对问题分别进行优化求解.实验设计考虑车辆恒速和早晚高峰影响车辆行驶速度的不同情况,比较不同算法的结果,以获取资源合理配置的解决方案.
This paper explores the vehicle routing problem for cash transportation by taking into account the workloads and costs. A real case in Shanghai is studied, and various factors, e.g. traffic jams are considered. In order to obtain a satisfactory solution, this paper has tested with the Solomon insertion heuristic algorithm, the neighborhood search heuristic, and the non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ). Simulation studies indicate that the neighborhood search heuristic outperforms the Solomon algorithm and NSGA-Ⅱwhen the speed of vehicles keeps changing under undesirable traffic conditions. But for instances with good traffic conditions, the NSGA-Ⅱgenerates a better result. Other aspects of the problem are also discussed for the purpose of offering suggestions and practicable method for decision making of practitioners and researchers.
作者
李明琨
柏高帅
蒋欣颖
LI Mingkun;BAI Gaoshuai;JIANG Xinying(School of Management,Shanghai University,Shanghai 200444,China)
出处
《上海大学学报（自然科学版）》
CAS
CSCD
北大核心
2019年第5期836-850,共15页
Journal of Shanghai University:Natural Science Edition
基金
上海浦江人才资助项目(13PJC064)
关键词
金融押运
模拟退火算法
遗传算法
工作量均衡
多目标优化
cash transportation
simulated annealing algorithm
genetic algorithm
workload balance
multi-objective optimization
