摘要
针对危险品车辆路径问题中车辆访问多个需求点的特性,在风险度量方式上考虑了运输过程中车辆载重量变化,建立了最小化总运输距离以及最小化总运输风险的双目标优化模型.采用改进的蚁群算法对模型进行求解并获得优化问题的非支配解,数值实验说明改进的风险度量方式更适合于危险化学品车辆路径问题,改进的蚁群算法能够有效率地对模型进行求解.
As the vehicles usually visit several demand points, we consider the variation of vehicle load on road system in hazardous material vehicle routing problem. A bi-objective optimization model minimizing the total travel distance and total travel risk is built. The model is solved by ant colony system and non-dominated solutions are got, the experiment results show that the new risk model is more adaptive to hazardous material vehicle routing problem and the ant colony system is effective in solving non-dominated solutions of the model.
出处
《数学的实践与认识》
北大核心
2016年第14期275-284,共10页
Mathematics in Practice and Theory
基金
国家自然科学基金(71171011
71571010
71301006)
新世纪优秀人才支持计划(NCET-12-0756)
关键词
车辆路径
危险品运输
风险度量
蚁群算法
vehicle routing
hazardous material transportation
risk measure
ant colony algorithm
