多周期库存路径问题及其算法研究
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摘要
经济全球化、信息化的快速发展,已经促使企业之间的竞争升级为供应链之间的竞争,如何协调多个企业在供应链中的合作是供应链管理必须解决的问题。供应商管理库存就是一种适应多个企业合作的供应链管理模式,它有利于实现资源优化配置和物流总成本控制。
库存和运输是物流系统的两大主要功能要素,二者的耗费约占物流总成本的2／3。库存路径问题整合库存和运输两大问题进行研究,是供应商管理库存必须解决的核心问题之一
通过对国内外相关文献研究,论文认为国内库存路径问题研究尚处在起步阶段,对复杂库存路径问题还缺乏系统、深入研究。从简单的单周期离散随机需求库存路径问题入手,通过改变需求特征、增加周期、加入频率限制、扩展层级等约束条件,重点研究了四类问题：单周期离散随机需求库存路径问题、短计划期随机需求库存路径问题、滚动多周期需求库存路径问题、多周期三层级库存路径问题,针对每类问题的成本构成分析建模、设计相应的启发式算法,并采用标准算例进行仿真试验。
研究的单周期离散随机需求库存路径问题在只考虑单次运输、订货(库存)的情况下,整合库存和运输路径问题进行优化。算例测试显示,库存路径问题整合效果受到车辆装载能力与单个零售商配送需求量的差别、运输总成本与库存成本差别的影响；需求特征的不同、运输条件的限制,会导致库存路径问题变化多样。运用均值(期望)处理的方法为短计划期随机需求库存路径问题建模,在讨论配送时点、配送量、配送优先次序后,零售商和配送中心均采用(s,S)库存策略,而配送方案根据当期库存、需求状态确定；设计一个启发式算法来搜索库存路径问题的满意解,运用计算机模拟随机需求的仿真测试证明,库存路径问题整合效果比一般的库存、运输的总成本估计效果要好。
提出用毗邻信息、动态候选集规模改进求解带装载能力约束的车辆路径问题的禁忌搜索算法,以提高其自适应能力。算例测试证明,改进的禁忌搜索算法可以为求解大规模问题(客户数量超过100)节省一半以上的搜索时间。借鉴一般的车辆路径问题建模思路,建立了滚动多周期策略的两层级库存路径问题模型。设计了基于贪婪思想的“大量调整”与只调整单个零售商不同时段配送量的“微调”相结合的局部邻域搜索方法。
在两层级库存路径问题研究基础上,加入物流中心进货约束,运用库存问题的建模思路,建立把配送分区看作“大零售商”需求点的整数倍周期-固定分区策略三层级库存路径问题模型。通过把三层级库存路径问题拆分成两部分,结合“基本库存路径问题”的总成本边界和配送分区策略,找出了两层级库存路径问题、三层级库存路径问题的总成本边界。在进行求解分析后,用固定分区配送成本与库存成本的比值作为指导,设计缩小计划期(中心进货期)搜索范围的启发式算法。仿真验证表明,整数倍周期-固定分区策略的效率在80%以上,而且优于“2的整数次幂”倍周期-固定分区策略。
The issue that how to coordinate many enterprises in the Supply Chain (SC) has become one of the vital points must be adressed in Supply Chain Management(SCM), beacause the competition among enterprises has been upgraded to that of SCs,being prompted by economic globalization and the rapid development of information technology. Vendor Managed Inventory (VMI) is a kind of model for adapting to collaration of multiple enterprises in SCM, which is useful in optimal allocatiing resources and cutting total logistics cost down.
Inventory and transportation are the two main functions of logistics system, their expenses occupy about 2/3 of total logistics cost.The Inventory Routing Problem (IRP) which integrating the two main functions is one of the vital points that must be addressed in VMI.
Based on studying relevant literature of IRP, the thesis claims that the researching on IRP in China is still in its initial stage,and lacks of deeply resraching on complex IRP. Starting from simple single-cycle IRP with discrete stochastic demand, and changing the constrains demand characteristics, or increasing planing period, or adding the frequency restrictions, or expansing level of topologyconstraints,four categories of practical IRPs, they are single-cycle IRP with discrete stochastic demand, short planning-period continuous-random demand IRP, rolling multi-cycle IRP, and multi-cycle three-echelon IRP, are analysesed in cost composition and modeling.Then the corresponding heuristic algorithms designed, and the models or algrithms are tested by some benchmarks.
Only one-time transportation and inventory is considered in optimizing the single-cycle discrete stochastic demand IRP. The example testing has shown that the IRP have great varity impacted by demand characteristics, and the gap between capacity of vehicle and demand, and the gap between transportation cost and inventory cost. Later, a method of mean (expected) processing for the short planning period continuous stochastic demand IRP is used for constructing its mathematical model. After discussing the distributing point of time, distributiing volume, distributing priorities, a huristics algrithm is proposed with (s,S) inventory policy both in Distribution Center (DC) and any retailer. The satisfactory solution for the simulation example of the short planning period continuous stochastic demand IRP declares that, the results get from the model and huristics algritm is better than that of simple mean processing approach.
Refered to a Tabu Search (TS)algrithm in literature for solving the Capacitated Vehicle Routing Problem (CVRP) proposed by a recent literature, and in order to improving its self-adapting property, an adjacent information and dynamically candidate-set size approach is designed for improving the TS algorithm.Test examples show that the modified TS algorithm is successful in saving about 50% of time when solving large-scale CVRP (the number of customers is more than 100). Learning from the general Vehicle Routing Problem (VRP) with modeling ideas, a rolling-period multi-cycle model is constructed for the two-echelon IRP, and base on "Greedy" ideas, a local search huristics algrithm is designed by using "maximum adjustment" and "minimum adjustment" alternately.
Finally, by adding ordering cost in DC,the IRP is expaned from two-echelon to three-echelon, and its mathmatic model is prompted, using the ideas of inventory problem, with grouping the retailers into multi clusters which are regarded as many "big-retailers",this policy is termed Integer-Ratio Fixed-Partition policy. Combined with the "basic IRP," the three-echelon IRP is devided into two sub-problems,and its lower or uper bound is derived.Conducting solving probability analysis, a huristics algrithm is designed with intger ratio of transportation cost to inventory cost or invers.The ratio is used to reduce the solution space and to direct searching the optimal solution, designed to reduce the planning period (center purchase period) heuristic search algorithm. Simulation shows that Integer-Ratio Fixed-Partition policy has an efficiency of 80% or more, and it's better than that of Power-of-Two Fixed-Partition policy.
库存和运输是物流系统的两大主要功能要素,二者的耗费约占物流总成本的2／3。库存路径问题整合库存和运输两大问题进行研究,是供应商管理库存必须解决的核心问题之一
通过对国内外相关文献研究,论文认为国内库存路径问题研究尚处在起步阶段,对复杂库存路径问题还缺乏系统、深入研究。从简单的单周期离散随机需求库存路径问题入手,通过改变需求特征、增加周期、加入频率限制、扩展层级等约束条件,重点研究了四类问题：单周期离散随机需求库存路径问题、短计划期随机需求库存路径问题、滚动多周期需求库存路径问题、多周期三层级库存路径问题,针对每类问题的成本构成分析建模、设计相应的启发式算法,并采用标准算例进行仿真试验。
研究的单周期离散随机需求库存路径问题在只考虑单次运输、订货(库存)的情况下,整合库存和运输路径问题进行优化。算例测试显示,库存路径问题整合效果受到车辆装载能力与单个零售商配送需求量的差别、运输总成本与库存成本差别的影响；需求特征的不同、运输条件的限制,会导致库存路径问题变化多样。运用均值(期望)处理的方法为短计划期随机需求库存路径问题建模,在讨论配送时点、配送量、配送优先次序后,零售商和配送中心均采用(s,S)库存策略,而配送方案根据当期库存、需求状态确定；设计一个启发式算法来搜索库存路径问题的满意解,运用计算机模拟随机需求的仿真测试证明,库存路径问题整合效果比一般的库存、运输的总成本估计效果要好。
提出用毗邻信息、动态候选集规模改进求解带装载能力约束的车辆路径问题的禁忌搜索算法,以提高其自适应能力。算例测试证明,改进的禁忌搜索算法可以为求解大规模问题(客户数量超过100)节省一半以上的搜索时间。借鉴一般的车辆路径问题建模思路,建立了滚动多周期策略的两层级库存路径问题模型。设计了基于贪婪思想的“大量调整”与只调整单个零售商不同时段配送量的“微调”相结合的局部邻域搜索方法。
在两层级库存路径问题研究基础上,加入物流中心进货约束,运用库存问题的建模思路,建立把配送分区看作“大零售商”需求点的整数倍周期-固定分区策略三层级库存路径问题模型。通过把三层级库存路径问题拆分成两部分,结合“基本库存路径问题”的总成本边界和配送分区策略,找出了两层级库存路径问题、三层级库存路径问题的总成本边界。在进行求解分析后,用固定分区配送成本与库存成本的比值作为指导,设计缩小计划期(中心进货期)搜索范围的启发式算法。仿真验证表明,整数倍周期-固定分区策略的效率在80%以上,而且优于“2的整数次幂”倍周期-固定分区策略。
The issue that how to coordinate many enterprises in the Supply Chain (SC) has become one of the vital points must be adressed in Supply Chain Management(SCM), beacause the competition among enterprises has been upgraded to that of SCs,being prompted by economic globalization and the rapid development of information technology. Vendor Managed Inventory (VMI) is a kind of model for adapting to collaration of multiple enterprises in SCM, which is useful in optimal allocatiing resources and cutting total logistics cost down.
Inventory and transportation are the two main functions of logistics system, their expenses occupy about 2/3 of total logistics cost.The Inventory Routing Problem (IRP) which integrating the two main functions is one of the vital points that must be addressed in VMI.
Based on studying relevant literature of IRP, the thesis claims that the researching on IRP in China is still in its initial stage,and lacks of deeply resraching on complex IRP. Starting from simple single-cycle IRP with discrete stochastic demand, and changing the constrains demand characteristics, or increasing planing period, or adding the frequency restrictions, or expansing level of topologyconstraints,four categories of practical IRPs, they are single-cycle IRP with discrete stochastic demand, short planning-period continuous-random demand IRP, rolling multi-cycle IRP, and multi-cycle three-echelon IRP, are analysesed in cost composition and modeling.Then the corresponding heuristic algorithms designed, and the models or algrithms are tested by some benchmarks.
Only one-time transportation and inventory is considered in optimizing the single-cycle discrete stochastic demand IRP. The example testing has shown that the IRP have great varity impacted by demand characteristics, and the gap between capacity of vehicle and demand, and the gap between transportation cost and inventory cost. Later, a method of mean (expected) processing for the short planning period continuous stochastic demand IRP is used for constructing its mathematical model. After discussing the distributing point of time, distributiing volume, distributing priorities, a huristics algrithm is proposed with (s,S) inventory policy both in Distribution Center (DC) and any retailer. The satisfactory solution for the simulation example of the short planning period continuous stochastic demand IRP declares that, the results get from the model and huristics algritm is better than that of simple mean processing approach.
Refered to a Tabu Search (TS)algrithm in literature for solving the Capacitated Vehicle Routing Problem (CVRP) proposed by a recent literature, and in order to improving its self-adapting property, an adjacent information and dynamically candidate-set size approach is designed for improving the TS algorithm.Test examples show that the modified TS algorithm is successful in saving about 50% of time when solving large-scale CVRP (the number of customers is more than 100). Learning from the general Vehicle Routing Problem (VRP) with modeling ideas, a rolling-period multi-cycle model is constructed for the two-echelon IRP, and base on "Greedy" ideas, a local search huristics algrithm is designed by using "maximum adjustment" and "minimum adjustment" alternately.
Finally, by adding ordering cost in DC,the IRP is expaned from two-echelon to three-echelon, and its mathmatic model is prompted, using the ideas of inventory problem, with grouping the retailers into multi clusters which are regarded as many "big-retailers",this policy is termed Integer-Ratio Fixed-Partition policy. Combined with the "basic IRP," the three-echelon IRP is devided into two sub-problems,and its lower or uper bound is derived.Conducting solving probability analysis, a huristics algrithm is designed with intger ratio of transportation cost to inventory cost or invers.The ratio is used to reduce the solution space and to direct searching the optimal solution, designed to reduce the planning period (center purchase period) heuristic search algorithm. Simulation shows that Integer-Ratio Fixed-Partition policy has an efficiency of 80% or more, and it's better than that of Power-of-Two Fixed-Partition policy.
引文
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