摘要
为提高应急物流系统的应急反应能力,论文针对需求随机变化的应急物流定位-路径问题,利用鲁棒优化的思想将灾区物资需求量表示为区间型数据,将应急救援过程划分为多个阶段,以总救援时间和系统总成本最小为目标,构建了多物资多运输车辆应急物流定位-路径优化模型,设计了改进的遗传算法对其进行求解。实例计算结果表明,该模型和算法可以有效地解决应急物流系统中需求随机变化的定位-路径问题,为政府机构应对重大突发事件提供科学的决策参考。
To improve the response capability of emergency logistics system , a stochastic demand location-routing problem in emergency logistics system is studied .Relief commodities requirements of demand points are presen-ted by intervals based on robust optimization and emergency relief procedures are divided into multi -stages, then the model of emergency location-routing problem with multi-materials multi-vehicles is developed to minimize the total system costs and total transportation time .An improved genetic algorithm is proposed to solve the model . The results show that the model and algorithm are effective for resolving the location-routing problem with stochastic demand in emergency logistics system , and it can provide scientific decision-making for government responding to major emergencies .
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2013年第6期45-51,共7页
Operations Research and Management Science
基金
国家自然科学基金资助项目(71203134)
国家自然科学基金重大研究计划培育项目(91024002)
教育部人文社会科学研究项目(10YJC630213)
关键词
应急物流
鲁棒优化
遗传算法
定位-路径问题
emergency logistics
robust optimization
genetic algorithm
location-routing problem
