物流服务供应链订单分配优化及其遗传算法  

Genetic Algorithm to Logistics Service Supply Chain Order Allocation Problem

作　　者：李姗姗[1] 

机构地区：[1]河南理工大学经济管理学院,河南焦作454000

出　　处：《运筹与管理》2014年第5期35-41,共7页Operations Research and Management Science

基　　金：国家自然科学基金资助项目(71272219);教育部人文社科基金规划项目(11YJA630067);河南省软科学研究项目(112400450285)

摘　　要：针对物流服务供应链订单分配问题中,物流服务集成商通常会按照所分配的订单价值向分包商收取一定比例交易费用的特点,设定交易费用为交易额的线性函数,构建了新的物流服务供应链订单分配优化混合整数规划模型,其优化目标为最小化交易费用、采购费用、短缺服务与延迟供给的物流能力数量。鉴于问题的NPhard特性,设计了相应的遗传算法,并结合基于优先权的启发式规则避免了大量非法初始解的出现。实验算例表明所建立的模型能够反映物流服务供应链订单分配过程中的线性交易费用因素,其所设计的算法能够在可接受的时间内获得质量较高的满意解,并且对于大规模订单分配优化问题,遗传算法的求解时间与求解结果要优于LINGO软件。The transaction costs are proportional to the transaction volume in LSSC order allocation problem .Con-sidering this characteristic , the transaction costs are expressed as linear function .A new mixed integer program-ming model for LSSC order allocation problem is established , so as to minimize the transaction costs , purchasing costs , rejected units and late delivered units .Because it is NP-hard in nature , a genetic algorithm combined with a heuristics rule is developed to solve the model and to avoid the illegal initial solutions .Random instances show that the model provides systemic simulation for the whole decision-making process and reflects the linear transac-tion costs factor .And the results of GA are stable and acceptable in allowable CPU time .Computational experi-ments show that the GA heuristic algorithm outperforms LINGO with respect to solution quality and computational time when the instances become larger .

关 键 词：供应链 混合整数规划模型 遗传算法 线性交易费用函数 订单分配 

分 类 号：F713.36[经济管理—产业经济]