供应链管理中的分销网络服务优化方法
|
摘要
分销是供应链管理的重要组成部分，分销决策与优化一直是企业界和学术界共同关注的热点问题。以往分销管理的相关研究大多以优化成本为目标，主要通过降低成本来提高企业的竞争力。近年来，产品同质化倾向日趋加深，市场逐渐转变为由客户主导的买方市场，客户对于服务的要求逐渐提高。在这种新的经济形势下，企业竞争的核心逐渐由降低成本转向争夺客户，如何在合理控制成本的同时实现高效益的服务已成为企业提高竞争力的关键。为此，本文以制造行业中一类较为典型的分销系统为研究对象，以提高分销服务性能为目标，综合运用运筹学理论和人工智能方法，针对不同决策层次的分销管理关键问题给出具体的优化策略、优化模型及求解方法。主要研究工作包括以下几个方面：
（1）首先分析分销服务的内涵，建立分销服务评价指标体系，总结分销服务水平的主要影响因素。以汽车等一类高级耐用消费品分销系统为研究对象，针对此类典型分销系统的特点及服务优化需求，提出本文的主要研究问题并进行深入分析，确定各分销服务优化问题的关键决策要素及决策准则。针对各问题的共同特点，提出基于差异性的服务优化策略以及基于多目标优化的问题求解方法，建立面向服务的分销系统整体优化方案，作为后续研究的基础。
（2）研究面向服务优化的多产品分销网络增量布局方法。基于不同客户区域、不同产品对于企业的不同重要程度，在计算分销系统整体服务水平时引入权重因子，强化重要客户区域、重要产品对整体服务水平的影响，研究基于模糊网络分析法的权重因子求解方法。进而以提高分销系统整体服务水平、降低相关成本为目标，建立多目标分销网络增量布局模型，对网络结构优化方案进行求解。针对模型的特点及复杂解结构，提出行列式编码与整数编码相结合的多段混合编码方法，并研究相关的多目标遗传求解过程。最后，通过仿真实验，从提高分销系统整体服务水平、保证关键个体服务水平、降低成本投入等方面对分销网络增量布局模型及求解算法的性能进行验证与分析。
（3）对分销系统末端销售商的库存决策与服务优化问题进行研究。针对销售商面临的客户的客观差异性，提出一种基于客户分群的库存控制策略，通过设置库存控制点来保证重要客户的服务优先权。针对库存过程的动态性和随机性，采用M/M/1排队模型描述销售商库存过程，通过求解排队模型的稳态解，确定库存系统的主要性能指标，进而建立基于客户分群的库存与服务优化模型。基于决策者的优化目标及偏好，在多目标模型中引入目标集和松弛项，研究基于目标到达法的库存参数求解算法。最后，通过仿真实验，从降低库存成本、提高客户准时服务率等方面对本文提出的策略、模型及算法的性能进行验证与分析。
（4）对随机环境下，一个分销中心、多个销售商组成的二级分销子系统中的缺货运作问题进行研究。根据各销售商的特点及不同的缺货概率，为分销中心各下属销售商设定不同的服务水平阈值区间，综合考虑应急转运和预防性转运，提出一种基于服务水平协调的联合转运机制，建立求解具体转运参数的多目标分销运作优化模型。为提高求解速度，保证缺货销售商的转入优先权，研究基于优先权排序的编码方法以及多目标Memetic算法。最后，通过仿真实验，从控制转运成本、降低服务延迟率、缩短服务延迟时间等方面对本文提出的转运机制、分销运作优化模型及求解算法的有效性进行验证与分析。
（5）基于本文提出的策略，模型及算法，设计并开发面向服务的供应链分销管理系统。结合哈尔滨哈飞汽车股份有限公司分销管理中的实际问题，给出应用案例与应用效果，从实际应用角度对本文的方法理论进行验证。
Distribution is an important part of supply chain management. Distributiondecision and optimization have attracted considerable attention from bothpractitioners and academics. Most of the previous researches focus on costreduction to improve the enterprise’s competitiveness. Recently, with thedevelopment of productivity and information technology, the degree of producthomogeneity is high and the market is currently a buyer’s market. Customers intoday’s marketplace are more demanding, not just of product quality, but also ofservice. Cost reduction is no longer the magic weapon to compete successfully, andthe enterprises come to realize the importance of customer service. In this regard, awidely used manufacturing distribution system is investigated in this thesis, sometypical distribution decision and the service optimization methods are proposedbased on operational research and artificial intelligence theory. The maincontribution of this thesis can be summarized as follows:
Firstly, the connotation of distribution service is expounded, the distributionservice level evaluation system is set up, and the main Influence factors areanalyzed. Then a widely used manufacturing distribution system is investigated.Based on its service optimization requirements, the research problems are presentedand the optimization rules are analyzed. Concerning the common characters of theseproblems, the differentiation based optimization strategy and the multi-objectiveoptimization methods are presented. Finally, a service-oriented optimizationsolution for the distribution system is proposed as the research foundation.
The service-oriented optimization method for redesigning distribution networkwith increments is studied. Weighting factors are employed to strengthen theinfluence of the important customer regions and products, and a new method isproposed to calculate the unitary service level of the distribution system. Based onthe fuzzy analytic network process, the weighting factors are calculated and then amulti-objective optimization model for distribution network reconfiguration isproposed. Concerning the character of the model and the complex nature of thesolution structure, a determinant code-based encoding structure is designed torepresent the problem, and a genetic algorithm-based solution procedure is developed. Simulation experiments and the comparisons are conducted to show theeffectiveness of the proposed method in improving unitary service level, keepingimportant customer’s service level, and reducing distribution cost.
Considering the optimization requirements of reducing the retailer's storagecost and improving customer service level, the single-product inventory systemwith stochastic demands and random replenishment intervals is studied. Based onthe service differentiation principle, inventory control point is introduced to ensurethe important customers' priority, and a new inventory control strategy based oncustomer segmentation is proposed. Then M/M/1queue system is established todescript the random inventory process. The inventory indices are calculated by thesteady state analysis, and the integration inventory optimization model based oncustomer segmentation is proposed. To deal with multi-objective and incorporatethe decision maker’s preferences in the decision process, goal set and relaxationitems are employed and the goal attainment method is used to solve the problem.Finally, simulation experiments and the comparisons are conducted to show theeffectiveness of the proposed method in reducing inventory cost and improving theon-time service rate.
To cope with the shortage problem of the sub distribution system, operationoptimization method is studied. Retailer differentiation is distinguished byintroducing service level threshold, an integrated lateral transshipment policy basedon service level adjustment is proposed, and a multi-objective mathematical modelis formulated to optimize the distribution operation process. To calculate thetransshipment policy variables, and to ensure the stock-out retailers' priority, themulti-objective memetic algorithm with priority-based encoding is developed.Finally, simulation experiments and the comparisons are conducted to show theeffectiveness of the proposed method in controlling transshipment cost, reducingservice delay rate, and shortening customer waiting time.
A service-oriented supply chain distribution management system is designedand implemented based on the strategies, models and algorithms proposed in thisthesis. Combining with the real problems in distribution management of HarbinHafei Automobile Industry Group Company LTD, the simulative application andresults are given to validate the theory and methods proposed in this thesis.
（1）首先分析分销服务的内涵，建立分销服务评价指标体系，总结分销服务水平的主要影响因素。以汽车等一类高级耐用消费品分销系统为研究对象，针对此类典型分销系统的特点及服务优化需求，提出本文的主要研究问题并进行深入分析，确定各分销服务优化问题的关键决策要素及决策准则。针对各问题的共同特点，提出基于差异性的服务优化策略以及基于多目标优化的问题求解方法，建立面向服务的分销系统整体优化方案，作为后续研究的基础。
（2）研究面向服务优化的多产品分销网络增量布局方法。基于不同客户区域、不同产品对于企业的不同重要程度，在计算分销系统整体服务水平时引入权重因子，强化重要客户区域、重要产品对整体服务水平的影响，研究基于模糊网络分析法的权重因子求解方法。进而以提高分销系统整体服务水平、降低相关成本为目标，建立多目标分销网络增量布局模型，对网络结构优化方案进行求解。针对模型的特点及复杂解结构，提出行列式编码与整数编码相结合的多段混合编码方法，并研究相关的多目标遗传求解过程。最后，通过仿真实验，从提高分销系统整体服务水平、保证关键个体服务水平、降低成本投入等方面对分销网络增量布局模型及求解算法的性能进行验证与分析。
（3）对分销系统末端销售商的库存决策与服务优化问题进行研究。针对销售商面临的客户的客观差异性，提出一种基于客户分群的库存控制策略，通过设置库存控制点来保证重要客户的服务优先权。针对库存过程的动态性和随机性，采用M/M/1排队模型描述销售商库存过程，通过求解排队模型的稳态解，确定库存系统的主要性能指标，进而建立基于客户分群的库存与服务优化模型。基于决策者的优化目标及偏好，在多目标模型中引入目标集和松弛项，研究基于目标到达法的库存参数求解算法。最后，通过仿真实验，从降低库存成本、提高客户准时服务率等方面对本文提出的策略、模型及算法的性能进行验证与分析。
（4）对随机环境下，一个分销中心、多个销售商组成的二级分销子系统中的缺货运作问题进行研究。根据各销售商的特点及不同的缺货概率，为分销中心各下属销售商设定不同的服务水平阈值区间，综合考虑应急转运和预防性转运，提出一种基于服务水平协调的联合转运机制，建立求解具体转运参数的多目标分销运作优化模型。为提高求解速度，保证缺货销售商的转入优先权，研究基于优先权排序的编码方法以及多目标Memetic算法。最后，通过仿真实验，从控制转运成本、降低服务延迟率、缩短服务延迟时间等方面对本文提出的转运机制、分销运作优化模型及求解算法的有效性进行验证与分析。
（5）基于本文提出的策略，模型及算法，设计并开发面向服务的供应链分销管理系统。结合哈尔滨哈飞汽车股份有限公司分销管理中的实际问题，给出应用案例与应用效果，从实际应用角度对本文的方法理论进行验证。
Distribution is an important part of supply chain management. Distributiondecision and optimization have attracted considerable attention from bothpractitioners and academics. Most of the previous researches focus on costreduction to improve the enterprise’s competitiveness. Recently, with thedevelopment of productivity and information technology, the degree of producthomogeneity is high and the market is currently a buyer’s market. Customers intoday’s marketplace are more demanding, not just of product quality, but also ofservice. Cost reduction is no longer the magic weapon to compete successfully, andthe enterprises come to realize the importance of customer service. In this regard, awidely used manufacturing distribution system is investigated in this thesis, sometypical distribution decision and the service optimization methods are proposedbased on operational research and artificial intelligence theory. The maincontribution of this thesis can be summarized as follows:
Firstly, the connotation of distribution service is expounded, the distributionservice level evaluation system is set up, and the main Influence factors areanalyzed. Then a widely used manufacturing distribution system is investigated.Based on its service optimization requirements, the research problems are presentedand the optimization rules are analyzed. Concerning the common characters of theseproblems, the differentiation based optimization strategy and the multi-objectiveoptimization methods are presented. Finally, a service-oriented optimizationsolution for the distribution system is proposed as the research foundation.
The service-oriented optimization method for redesigning distribution networkwith increments is studied. Weighting factors are employed to strengthen theinfluence of the important customer regions and products, and a new method isproposed to calculate the unitary service level of the distribution system. Based onthe fuzzy analytic network process, the weighting factors are calculated and then amulti-objective optimization model for distribution network reconfiguration isproposed. Concerning the character of the model and the complex nature of thesolution structure, a determinant code-based encoding structure is designed torepresent the problem, and a genetic algorithm-based solution procedure is developed. Simulation experiments and the comparisons are conducted to show theeffectiveness of the proposed method in improving unitary service level, keepingimportant customer’s service level, and reducing distribution cost.
Considering the optimization requirements of reducing the retailer's storagecost and improving customer service level, the single-product inventory systemwith stochastic demands and random replenishment intervals is studied. Based onthe service differentiation principle, inventory control point is introduced to ensurethe important customers' priority, and a new inventory control strategy based oncustomer segmentation is proposed. Then M/M/1queue system is established todescript the random inventory process. The inventory indices are calculated by thesteady state analysis, and the integration inventory optimization model based oncustomer segmentation is proposed. To deal with multi-objective and incorporatethe decision maker’s preferences in the decision process, goal set and relaxationitems are employed and the goal attainment method is used to solve the problem.Finally, simulation experiments and the comparisons are conducted to show theeffectiveness of the proposed method in reducing inventory cost and improving theon-time service rate.
To cope with the shortage problem of the sub distribution system, operationoptimization method is studied. Retailer differentiation is distinguished byintroducing service level threshold, an integrated lateral transshipment policy basedon service level adjustment is proposed, and a multi-objective mathematical modelis formulated to optimize the distribution operation process. To calculate thetransshipment policy variables, and to ensure the stock-out retailers' priority, themulti-objective memetic algorithm with priority-based encoding is developed.Finally, simulation experiments and the comparisons are conducted to show theeffectiveness of the proposed method in controlling transshipment cost, reducingservice delay rate, and shortening customer waiting time.
A service-oriented supply chain distribution management system is designedand implemented based on the strategies, models and algorithms proposed in thisthesis. Combining with the real problems in distribution management of HarbinHafei Automobile Industry Group Company LTD, the simulative application andresults are given to validate the theory and methods proposed in this thesis.
引文
[1] Petrovic D, Xie Y, Burnham K, et al. Control of Distribution Supply Chainsin the Presence of Fuzzy Customer Demand [J]. European Journal ofOperational Research,2008(185):146–158.
[2] Segerstedt A, Olofsson T. Supply Chains in the Construction Industry [J].Supply Chain Management: An International Journal,2010(15):347-353.
[3] Shingeo S. Non-Stock Production: The Shingo System for ContinuousImprovement [M]. Cambridge, MA: Productivity Press,1988.
[4] Houlihan J B. International Supply Chain Management [J]. InternationalJournal of Physical Distribution&Logistics Management,1987,17(2):51-66.
[5] Christopher M. Logistics and Supply Chain Management [M]. London:Pitman,2003.
[6] Stevens G C. Integrating the Supply Chain [J]. International Journal ofPhysical Distribution&Logistics Management,1989,19(8):3-8.
[7] Lee H L, Billington C. The Evolution of Supply-Chain-Management Modelsand Practice at Hewlett-Packard [J]. Interfaces,1995,25(5):42-63.
[8] Lambert DM, Cooper MC, Pagh JD. Supply Chain Management:Implementation Issues and Research Opportunities [J]. International Journalof Logistics Management,1998,9(2):1-20.
[9] Paul R M J, Donald F W. Contemporary Logistics [M], New Jersey: PrenticeHall,2010.
[10] Bilgen B, Ozkarahan I. Strategic Tactical and OperationalProduction-distribution Models: a Review [J]. International Journal ofTechnology Management,2004,(1):151-171
[11] Newell G F. Scheduling, Location, Transportation and Continuum Mechanics:Some Simple Approximations to Optimization Problems [J]. SIAM Journalof Applied Mathematics,1973(25):346-360.
[12] Novaes A G N, Cursi J E, Graciolli O D. A Contimuous Approach to theDesign of Physical Distribution [J]. Computers&Operations Research,2000(27):877-893.
[13] Dasci A, Verter V. A Continuous Model for Production-Distribution SystemDesign [J]. European Journal of Operational Research,2001(129):287-298.
[14]张长星,党延忠.供应商管理库存环境下的分销网络连续近似模型[J].管理工程学报,2005,19(2):50-54.
[15]姜大立,杨西龙.易腐物品配送中心连续选址模型及其遗传算法[J],系统工程理论与实践.2003,23(2):62~67.
[16]张长星,党延忠.分销网络设计的连续近似模型[J].系统工程学报.2003,18(5):447-451.
[17] Melkote S. Daskin M S. Capacitated Facility Location Network DesignProblems [J]. European Journal of Operational Research.2001,129(3):481-495.
[18] Min H, Ko H J, Park B I. A Lagrangian Relaxation Heuristic for Solving theMulti-echelon, Multi-commodity, Close-loop Supply Chain Network DesignProblem [J]. International Journal of Logistics Systems and Management.2005,1(4):382-404.
[19] Cordeau J F, Pasin F, Solomon M M. An Integrated Model for LogisticsNetwork Design [J]. Annuals of Operation Research.2006,144(12):59-82.
[20] Lee D H and Dong M. Dynamic Network Design for Reverse LogisticsOperations under Uncertainty [J]. Transportation Research Part E: Logisticsand Transportation Review,2009,45(1):506-522.
[21] Chan F T S, Chung S H. A Multi-criterion Genetic Algorithm for OrderDistribution in a Demand Driven Supply Chain [J]. International Journal ofComputer Integrated Manufacturing,2004,17(4):339–351.
[22] Zahir S, Sarker R. Optimising Multi-objective Location Decisions in aSupply Chain using an AHP-enhanced Goal-programming Model [J].International Journal of Logistics Systems and Management,2010,6(3):249-266.
[23]赵晓煜,汪定伟.供应链中二级分销网络的优化设计模型[J].管理科学学报,2001,4(4):22-26.
[24] Altiparmak F, Gen M, Lin L, et al. A Steady-state Genetic Algorithm forMulti-product Supply Chain Network Design [J]. Computers&IndustrialEngineering,2009(56):521-537.
[25]金海河,陈剑.分销配送网络优化模型及求解算法[J].清华大学学报,2002,42(6):739-742.
[26]谭凌,高峻峻,王迎军.基于库存成本优化的配送中心选址问题研究[J].系统工程学报,2004,19(1):59~65.
[27] Melo M T, Nickel S, Saldanha-da-Gama F. Dynamic Multi-commodityCapacitated Facility Location: A Mathematical Modeling Framework forStrategic Supply Chain Planning [J]. Computers and Operations Research,2006(33):181-208.
[28] Dias J, Captivo M E, Climaco J. Capacitated Dynamic Location Problemswith Opening, Closure and Reopening of Facilities [J]. IMA Journal ofManagement Mathematics,2006(17):317-348.
[29] Thanha P N, Bostelb N, Péton O. A Dynamic Model for Facility Location inthe Design of Complex Supply Chains [J]. International Journal ofProduction Economics,2008(113):678-693.
[30] Melachrinoudis E, Min H. The Dynamic Relocation and Phase-out of aHybrid, Two-echelon Plant/Warehousing Facility: A Multiple ObjectiveApproach [J]. European Journal of Operational Research,2000(123):1-15.
[31]翟恩东,汪定伟.考虑库存分配的多年度二级分销网络优化模型[J].东北大学学报,2001,22(2):175-178.
[32]狄卫民,胡培.制造/在制造物流网络优化设计的多周期静态选址模型[J].中国机械工程,2008,19(16):1950-1954.
[33]税文兵,叶怀珍,张诗波.物流配送中心动态选址模型及算法研究[J].计算机应用研究,2010,27(12):4476-4479.
[34] Vorst J, Tromp S, and Zee D. A Simulation Environment for the Redesign ofFood Supply Chain Networks Modeling Quality Controlled Logistics [C].Proceedings of the37th Conference on Winter Simulation, Orlando, FL,2005:1658-1667.
[35] Farahani R Z, Elahipanah M. A Genetic Algorithm to Optimize the TotalCost and Service Level for Just-in-time Distribution in a Supply Chain [J].International Journal of Production Economics,2008(111):229-243.
[36] Melachrinoudis E, Min H. Redesigning a Warehouse Network [J]. EuropeanJournal of Operational Research,2007(176):210-229.
[37] Kaplan U, Türkay M, Karas zen B, Biegler LT. Optimization of SupplyChain Systems with Price Elasticity of Demand [J]. Informs journal oncomputing,2011,23:557–568.
[38] Harris F W. How Many Parts to Make at Once [J]. The Magazine ofManagement,1913,10(2):135-136.
[39] Whitin T M. Inventory Control and Price Theory [J]. Management Science,1995,2(1):61-80.
[40] Clark A J, Scarf H. Oprtinal Policies of a Multi-eshelon Inventory Problem[J]. Management Science,1960,6(4):475-490.
[41] Graves S C. A Multi-echelon Inventory Model with Fixed ReplenishmentIntervals [J]. Management Science,1996,42(1):1-18.
[42] Chen F, Zheng Y S. One Warehouse Multi-retailer Systems with CentralizedStock Information [J]. Operations Research,1997(45):275-287.
[43] Dong L, Lee H L. Optimal Policies and Approximations for a SerialMultiechelon Inventory System with Time-correlated Demand [J].Operations Research,2003,51(6):96-99.
[44] Chel K P, Niel U. Simulation-based Optimization of Multi-echlon InventorySystems [J]. International Journal of Production Economics,2005(93-94):505-51.
[45]张钦,沈厚才,达庆利.供应链管理：两级分销系统的最优订货策略[J].系统工程学报,2002,17(4):303-308.
[46]高峻峻,王迎军,郭亚军.需求不确定的分销系统最小成本模型[J].东北大学学报,2002,23(1):87-90.
[47]卫忠,徐晓飞,战德臣,等.协同供应链多极库存控制的多目标优化模型及求解方法[J].自动化学报,2007,33(2):181-187.
[48]胡建国,冯恩民,郭华.随机需求条件下分销系统协同库存策略研究[J].大连理工大学学报,2009,49(2):288-293.
[49]王正元,宋建社,何志德,等.一种备件多极库存系统的仿真优化模型[J].系统仿真学报,2007,19(5):1003-1006.
[50] Hariga M. An EOQ Lot Sizing Model with Random Supplier Capacity [J].International Journal of Production Economics,1999(59):39-47.
[51] Zipkin P H. Foundations of Inventory Management [M]. Boston:McGraw-Hill,2000.
[52]郭强.对具有库存损耗的EOQ模型的研究[J].系统工程,2004,22(7):17-19.
[53]柏庆国,张玉忠,徐健腾.易变质产品在带运输时间的二级供应链中的订购策略研究[J].管理学报,2011,8(2):294-300.
[54] Ritchie E. Practical Inventory Replenishment Policies for a Linear TrendDemand [J]. Journal of Operational Research Society,1980(33):605-613.
[55] Wee H M. Economic Production Lot Size Model for Deterioration Items withPartial Backordering [J]. Computers and Industrial Engineering,1993,(24):449-458.
[56]罗兵,黄波,卢娜.一种线性时变需求且短缺量部分拖后的VMI模型[J].系统工程理论与实践,2006,26(5):36-41.
[57]张捍东,王青云,岑豫皖.弹性需求条件下具有库存损耗的经济订货批量模型[J].计算机集成制造系统,2009,15(8):1528-1533.
[58] Moon I, Gallego G. Distribution Free Procedures for Some Inventory Models[J]. The Journal of the Operational Research Society,1994,45(6):651-658.
[59] Andersson J, Axs ter S, Marklund J. Decentralized Multi-echelon InventoryControl [J]. Production and Operations Management,1998(7):370-386.
[60] Axs ter S. A Framework for Decentralized Multi-echelon Inventory Control[J]. IIE Transactions,2001,33:91-97.
[61] Strijbosch L W G, Moors J J A. The Impact of Unknown Demand Parameterson (R, S) Inventory Control Performance [J]. European Journal ofOperational Research,2005,162(1):805-815.
[62] Wensing T. Periodic Review Inventory Systems [M]. New York: Springer,2011.
[63]马士华,林勇.基于随机提前期的（Q,r）库存模型[J].计算机集成制造系统,2002,8(5):396-398.
[64]高峻峻,王迎军,郭亚军,等.一类随机需求下分销系统的主从对策模型即仿真[J].系统管理学报,2007,16(3):230-236.
[65]刘保政,汪定伟.连锁营销下随机需求的分销系统双层补货优化控制模型[J].控制与决策,2010,25(5):735-739.
[66] Veinott J A F. Optimal Policy in a Dynamic, Single Product, Non-stationaryInventory Model with Several Demand Classes [J]. Operations Research,1965(13):761–778.
[67] Topkis D M. Optimal Ordering and Rationing Policies in a Non-stationaryDynamic Inventory Model with n Demand Classes [J]. Management Science,1968(15):160-176.
[68] Frank K C, Zhang R Q, Duenyas I. Optimal Policies for Inventory Systemswith Priority Demand Classes [J]. Operations Research,2003,51(6):993-1002.
[69] Sen A, Zhang A X. The Newsboy Problem with Multiple Demand Classes [J].IIE T ransaction,1999(31):431-444.
[70] Ding Q, Kouvelis P, Milner J M. Dynamic Pricing through Discounts forOptimizing Multiple-class Demand Fulfillment [J]. Operations Research,2006(1):169-183.
[71] Ding Q, Kouvelis P, Milner J M. Dynamic Pricing for Multiple ClassDeterministic Demand Fulfillment [J]. IIE Transactions,2007(39):997-1013.
[72]裘民民,赵晓波,王建才.基于(s,S)库存策略的分销系统最优分配问题[J].清华大学学报(自然科学版),2006,46(5):749-752.
[73]汪达钦,霍佳震.有限时域下多需求类型产品的库存策略[J].系统工程理论与实践,2010,30(6):981-986.
[74]汪小京,刘志学,郑长征.多类顾客环境下报童模型中库存分配策略研究[J].中国管理科学,2010,18(4):65-72.
[75]汪小京,刘志学,郑长征.周期性补货系统中多类顾客的库存分配策略[J].武汉理工大学学报,2010,32(4):661-667.
[76] Nahmias S, Demmy S. Operating Characteristics of an Inventory Systemwith Rationing [J]. Management Science,1981(27):1236–1245.
[77] Moon I, Kang S. Rationing Policies for Some Inventory Systems [J]. Journalof Operation Research Socioty,1998(49):509-518.
[78] Dekker R, Kleijn M J, Rooij P J. A Spare Parts Stocking System based onEquipment Criticality [J]. International Journal of Production Economics,1998,56(7):69-77.
[79] Ha A Y. Inventory Rationing in a Make-to-Stock Production System withSeveral Demand Classes and Kost Sales [J]. Management Science,2000,43(8):1093-1103.
[80] Melchiors P, Dekker R, Kleijn M. Inventory Rationing in an (s, Q) InventoryModel with Lost Sales and Two Demand Classes [J]. Journal of OperationResearch Socioty,2000,51(1):11–122.
[81] Sapna I K P. An (S,Q) Markovian Inventory System with Lost Sales and TwoDemand Classes [J]. Mathematical and Computer Modelling,2006(43):687-694.
[82]刘文丽,王欣宇.代发货环境下网络销售商的阈值库存分配策略[J].系统工程学报,2008,23(6):650-658.
[83]周伟华,吴晓波,杜健.服务多类需求串行供应链的最优控制策略[J].管理科学学报,2010,13(3):19-28.
[84] Laporte G. Fifty Years of Vehicle Routing [J]. Transportation Science,2009(43):408-416.
[85] Mendoza J E, Casranier B, Guéret C, et al. A Memetic Algorithm for theMulti-compartment Vehicle Routing Problem with Stochastic Demands [J].Computers&Operations Research,2010(37):1886-1898.
[86] Thomas D J, Griffin P M. Coordinated Supply Chain Management [J].European Journal of Operational Research,1996(94):1-15.
[87]熊峰.供应链协同调度研究[D].武汉:武汉理工大学博士学位论文,2009.
[88]姚珣.不确定性下的供应链协调机制及其应急管理研究[D].成都:电子科技大学,2009.
[89] Rathi A K, Church R L, Solanki R S. Allocation Resources to Support aMulti Commodity Flow with Time Windows [J]. Logisitics andTransportation Review,1993(28):167-188.
[90] Equi L, Gallo G, Marziale S, et al. A Combined Transportation andScheduling Problem [J]. European Joumal of Operational Research,1997(97):94-104.
[91] Hong S C, Park Y B. A Heuristic for Bi-objective Vehicle Routing with TimeWindow Constraints [J]. International Journal of Production Economics,1999(62):249-258.
[92] Yang S, Hamedi M, Haghani A. Online Dispatching and Routing Model forEmergency Vehicles with Area Coverage Constraints [J]. TransportationResearch Record: Journal of the Transportation Research Board,2005(1923):1-8.
[93]任文君,孙利辉,李霞.基于缺货损失的配送中心调度在线策略[J].系统工程,2010,28(10):114-117.
[94] Li L, Lee Y. Pricing and Delivery-time Performance in a CompetitiveEnvironment [J]. Management Science,1994,40(5):633-646.
[95] Palaka K, Erlebacher S, Kropp D H. Lead Time Setting, Capacity Utilization,and Pricing Decisions under Lead Time Dependent Demand [J]. IIETransactions,1998(30):151-163.
[96] Ernst R, Kamrad B. Allocation of Warehouse Inventory with Electronic DataInterchanges and Fixed Order Intervals [J]. European Journal of OperationalResearch,1997(103):117-128.
[97] Boyaci T, Ray S. Production Differentiation and Capacity Cost Interaction inTime and Price Sensitive Demand [J]. Manufacturing&Service OperationsManagement,2003(5):18-36.
[98] Qi X T, Bard J F, Yu G. Supply Chain Coordination with DemandDisruptions [J]. Omega,2004,32(4):301-312.
[99] Chan F T S, Chan H K. A Simulation Study with Quantity Flexibility in aSupply Chain Subjected to Uncertainties [J]. International Journal ofComputer Integrated Manufacturing,2006,19(2):148-160.
[100]于辉,陈剑,于刚.批发价契约下的供应链应对突发事件[J].系统工程理论与实践,2006,8(8):33-41.
[101]戢守峰,杜晓璐,黄小原.协同商务下分销系统紧急补货模型与分析[J].东北大学学报,2007,28(5):753-756.
[102] Axs ter S. Modeling Emergency Lateral Transshipments in InventorySystems [J]. Management Science,1990(36):1329-1338.
[103] Lee H L.A. Multi-echelon Inventory Model for Repairable Items withEmergency Lateral Transshipments [J]. Management Science,1987(33):1302-1316.
[104] Zhao H, Deshpande V. Inventory Sharing and Rationing IndecentralizedDealer Networks [J]. Management Science,2005,51(4):531–547.
[105] Herer Y T, Tzur M, Yucesan E. The Multilocation Transshipment Problem [J].IIE Transactions,2006(38):185–200.
[106]李怡娜,徐学军.双分销渠道下短生命周期产品供应链转运策略[J].计算机集成制造系统,2010,16(1):155-164.
[107] Tagaras G. Pooling in Multi-location Periodic Inventory DistributionSystems [J]. Omega,1999(27):39-59.
[108] Banerjee A, Burton J, Banerjee S. A Simulation Study of Lateral Shipmentsin Single Supplier, Multiple Buyers Supply Chain Networks[J]. InternationalJournal of Production Economics,2003(81–82):103–114.
[109]李晓宏,孙林岩,李刚.不确定性需求下易逝品销售商横向调货策略研究[J].运筹与管理,2009,18(5):76-80.
[110] Tiacci L, Saetta S. A Heuristic for Balancing the Inventory Level of DifferentLocations through Lateral Shipments [J]. International Journal of ProductionEconomics,2010,131(1):1-9.
[111]孙会君,高自友.基于双层规划的供应链二级分销网络优化设计模型[J].管理工程学报,2004,18(1):68-71.
[112]刘昱岗,郝光,罗霞.基于模糊多目标格序决策的分销网络优化模型[J].系统工程,2006,24(7):16-20.
[113]李良,康杰,喻伟.顾客选择行为与库存[J].系统工程,2003,21(1):86-89.
[114]刘蕾,唐小我.订货提前期对服务水平决策的影响研究[J].控制与决策,2005,20(11):1265-1268.
[115] Lee J K, Larry L P. Operations Management Strategy and Analysis [M]. NewJersey: Prentice Hall,2002.
[116] Yan H, Yu Z, Edwin Cheng T C. A Strategic Model for Supply Chain Designwith Logical Constraints: Formulation and Solution [J]. Computers andOperations Research,2003(30):2135-2155.
[117] Biswas S, Narahari Y. Object Oriented Modeling and Decision Support forSupply Chains [J]. European Journal of Operational Research,2004(153):704-726.
[118]马士华,林勇,陈志祥.供应链管理[M].北京:机械工业出版社,2000.
[119]徐晓飞,王忠杰,莫同.服务工程方法体系[J].计算机集成制造系统,2007,13(8):1457-1464.
[120]刘作仪,杜少甫.服务科学管理与工程:一个正在兴起的领域[J].管理学报,2008,5(4):607-615.
[121] Hill T P. On Goods and Services [J]. The Review of Income and Wealth.1997,23(4):315-338.
[122] IBM Research. Services Science, Management and Engineering-ServicesDefinition [EB/OL]. http://www. research. ibm. com/ssme/services. shtml.2008.
[123] M. Christopher.物流与供应链管理：降低成本与改善服务的战略（英文版）[M].北京:电子工业出版社,2003.
[124] Gr nroos C. Service Management: A Management Focus for ServiceCompetition [J]. International Journal of Service Industry Management,1990,1(1):6-14.
[125] Gadrey J. Productivity, Innovation and Knowledge in Services: NewEconomic and Socio-Economic Approaches [M]. Cheltenham, UK: EdwardElgar Publisher,2002.
[126]朱丹.供应链应急物流系统构建研究[J].北京交通大学学报.2011,10(2):59-64.
[127] Laporte G. Vehichle Routing: Methods and Studies [M]. Amsterdam:North-Holland,1998.
[128] Donald W F, John H B, Thomas R H. Production&Inventory Management[M]. Cincinnati, OH: South-Western Pub. Co.,1991.
[129] Zhou A, Qu B, Li H, Zhao S. Multiobjective evolutionary algorithms: Asurvey of the state of the art [J]. Swarm and Evolutionary Computation,2011(1):32–49.
[130] Saaty T L. Decision Making with Dependence and Feedback [M]. Pittsburgh,PA., USA: RWS Publication,1996.
[131] Zhang X, Wang C. Application of Analytic Network Process in AgriculturalProducts Logistics Performance Evaluation [J].Innovative Computing andInformation,2011(231):500-506.
[132] Amin S H, Zhang G. An Integrated Model for Closed-loop Supply ChainConfiguration and Supplier Selection: Multi-objective Approach [J]. ExpertSystems with Applications,2012,39(8):6782-6791.
[133] elebi D, Bayraktar D, Bing l L. Analytical Network Process for LogisticsManagement: A Case Study in a Small Electronic Appliances Manufacturer[J]. Computers&Industrial Engineering,2010,58(3):432-441.
[134] Ludmil M, Madan G S. Fuzzy Analytic Network Process and its Applicationto the Development of Decision Support Systems [J]. IEEE Transactions onSystems, Man, and Cybernetics-Part C: Applications and Reviews,2003,33(1):33-41.
[135] Cheng C H, Mon D L. Evaluating Weapon System by Analytical HierarchyProcess based on Fuzzy Scales [J]. Fuzzy Sets and Systems,1994(63):1-10.
[136] Hnaien F, Delorme X, Dolgui A. Multi-objective Optimization for InventoryControl in Two-level Assembly Systems under Uncertainty of Lead Times [J].Computer and Operations Research,2010(37):1835-1843.
[137] Ko H, and Evans G. A Genetic Algorithm-based Heuristic for the DynamicIntegrated Forward/Reverse Logistics Network for3pls [J]. Computers andOperations Research,2007(34):346–366.
[138] Gen M, Cheng R. Genetic Algorithms and Engineering Optimization [M].New York: Wiley,2000.
[139] Prüfer H. Neuer Beweis Eines Satzes über Permutationen [J]. Archives ofMathematical Physics,1918(27):142-144.
[140] Syarif A, Yun Y S, Gen M. Study on Multi-stage Logistic Chain Network: ASpanning Tree-based Genetic Algorithm Approach [J].Computers&Industrial Engineering,2002(43):299-314.
[141] Gen M, Kumar A, Kim J R. Recent Network Design Techniques usingEvolutionary Algorithms [J]. International Journal of Production Economics,2005(98):251-261.
[142] Krishnamoorthy M, Ernst A T, Sharaiha Y M. Comparison of Algorithms forthe Degree Constrained Minimum Spanning Tree [J]. Journal of Heuristics,2001(7):587-611.
[143] Yeh W C. Ahybrid Heuristic Algorithm for the Multistage Supply ChainNetwork Problem [J]. Internal Journal of Advanced ManufacturingTechnology,2005(26):675-685.
[144] Abuali F N, Wainwright R L, Schoenefeld D A. Determinant Factorization: ANew Encoding Scheme for Spanning Trees Applied to the ProbabilisticMinimum Spanning Tree Problem [C]. Proceedings of the Sixth InternationalConference on Genetic Algorithms, SanMateo, CA: Morgan Kaufmann,1995:470-477.
[145] Chou H, Premkumar G, Chu C H. Genetic Algorithm for CommunicationsNetwork Design: an Empirical Study for the Factors that InfluencePerformance [J]. IEEE Transactions on Evolutionary Computation,2001,5(3):236-249.
[146] Yao M J, Hsu H W. A New Spanning Tree-based Genetic Algorithm for theDesign of Multi-stage Supply Chain Network with Nonlinear TransportationCosts [J]. Optimizationand Engineering,2009,10(2):219-37.
[147] Wang H F, Hsu H W. A Closed-loop Logistic Model with a Spanning-treebased Genetic Algorithm [J]. Computers&Operations Research,2010(37):376-389.
[148]蒋绍忠.管理运筹学教程[M].杭州:浙江大学出版社,2005:292-319.
[149] Boch G, Greiner S. Queueing Networks and Markov Chains Modeling andPerformance Evaluation with Computer Science Applications [M]. NewJersey: John Wiley&Sons, Inc,2006.
[150] Gembicki F W, Haimes Y Y. Approach to Performance and SensitivityMulti-objective Optimization: the Goal Attainment Method [J]. IEEETransactions on Automatic Control,1975,20(6):769–771.
[151] Charnes A, Cooper W W, Ferguson R. Optimal Estimation of ExecutiveCompensation by Linear Programming [J]. Management Science,1955,1(2):138-151.
[152] Goh C K, Ong Y S, and Tan K C. Multi-Objective Memetic Algorithms [M].New York: Springer,2010.
[153] Yeh W C. An Efficient Memetic Algorithm for the Multi-stage Supply ChainNetwork Problem [J]. International Journal of Advanced ManufacturingTechnology,2005,29(7-8):803-813.
[154] Boudia M, Prins C. A Memetic Algorithm with Dynamic PopulationManagement for an Integrated Production–distribution Problem [J].European Journal of Operational Research,2009(195):703–15.
[155] ElMekkawy T Y, Liu S. A New Memetic Algorithm for Optimizing thePartitioning Problem of Tandem AGV Systems [J]. International Journal ofProduction Economics,2009,118(2):508–20.
[156] Joana D, Captivo M E, Clímaco J. A Memetic Algorithm for Multi-objectiveDynamic Location Problems [J]. Journal of Global Optimization,2008(42):221–253.
[157] Gen M, Altiparmak F, Lin L. Agenetic Algorithm for Two-stageTransportation Problem using Priority-based Encoding [J]. OR Spectrum,2006,28(7):337-354.
[158] Ishibuchi H, Murata T. A Multiobjective Genetic Local Search Algorithmand Its Application to Flowshop Scheduling [J]. IEEE Transactions onSystems, Man and Cybernetics,1998,28(3):392–403.
[159] Bertsimas D J, Chervi P, Peterson M. Computational Approaches toStochastic Vehicle Routing Problems [J]. Transportation Science,1995,29(4):342–352.
[160] Ishibuchi H, Yoshida T, Murata T. Balance between Genetic Search andLocal Search in Memetic Algorithms for Multi objective Permutation Flowshop Scheduling [J]. IEEE Transactions on Evolutionary Computation,2003,7(2):204-223.
[161] Knowles J, Corne D. A Memetic Algorithm for Multiobjective Optimization[C]. Proceedings of the Congress on Evolutionary Computation, New Jersey,2000:325-332.
[2] Segerstedt A, Olofsson T. Supply Chains in the Construction Industry [J].Supply Chain Management: An International Journal,2010(15):347-353.
[3] Shingeo S. Non-Stock Production: The Shingo System for ContinuousImprovement [M]. Cambridge, MA: Productivity Press,1988.
[4] Houlihan J B. International Supply Chain Management [J]. InternationalJournal of Physical Distribution&Logistics Management,1987,17(2):51-66.
[5] Christopher M. Logistics and Supply Chain Management [M]. London:Pitman,2003.
[6] Stevens G C. Integrating the Supply Chain [J]. International Journal ofPhysical Distribution&Logistics Management,1989,19(8):3-8.
[7] Lee H L, Billington C. The Evolution of Supply-Chain-Management Modelsand Practice at Hewlett-Packard [J]. Interfaces,1995,25(5):42-63.
[8] Lambert DM, Cooper MC, Pagh JD. Supply Chain Management:Implementation Issues and Research Opportunities [J]. International Journalof Logistics Management,1998,9(2):1-20.
[9] Paul R M J, Donald F W. Contemporary Logistics [M], New Jersey: PrenticeHall,2010.
[10] Bilgen B, Ozkarahan I. Strategic Tactical and OperationalProduction-distribution Models: a Review [J]. International Journal ofTechnology Management,2004,(1):151-171
[11] Newell G F. Scheduling, Location, Transportation and Continuum Mechanics:Some Simple Approximations to Optimization Problems [J]. SIAM Journalof Applied Mathematics,1973(25):346-360.
[12] Novaes A G N, Cursi J E, Graciolli O D. A Contimuous Approach to theDesign of Physical Distribution [J]. Computers&Operations Research,2000(27):877-893.
[13] Dasci A, Verter V. A Continuous Model for Production-Distribution SystemDesign [J]. European Journal of Operational Research,2001(129):287-298.
[14]张长星,党延忠.供应商管理库存环境下的分销网络连续近似模型[J].管理工程学报,2005,19(2):50-54.
[15]姜大立,杨西龙.易腐物品配送中心连续选址模型及其遗传算法[J],系统工程理论与实践.2003,23(2):62~67.
[16]张长星,党延忠.分销网络设计的连续近似模型[J].系统工程学报.2003,18(5):447-451.
[17] Melkote S. Daskin M S. Capacitated Facility Location Network DesignProblems [J]. European Journal of Operational Research.2001,129(3):481-495.
[18] Min H, Ko H J, Park B I. A Lagrangian Relaxation Heuristic for Solving theMulti-echelon, Multi-commodity, Close-loop Supply Chain Network DesignProblem [J]. International Journal of Logistics Systems and Management.2005,1(4):382-404.
[19] Cordeau J F, Pasin F, Solomon M M. An Integrated Model for LogisticsNetwork Design [J]. Annuals of Operation Research.2006,144(12):59-82.
[20] Lee D H and Dong M. Dynamic Network Design for Reverse LogisticsOperations under Uncertainty [J]. Transportation Research Part E: Logisticsand Transportation Review,2009,45(1):506-522.
[21] Chan F T S, Chung S H. A Multi-criterion Genetic Algorithm for OrderDistribution in a Demand Driven Supply Chain [J]. International Journal ofComputer Integrated Manufacturing,2004,17(4):339–351.
[22] Zahir S, Sarker R. Optimising Multi-objective Location Decisions in aSupply Chain using an AHP-enhanced Goal-programming Model [J].International Journal of Logistics Systems and Management,2010,6(3):249-266.
[23]赵晓煜,汪定伟.供应链中二级分销网络的优化设计模型[J].管理科学学报,2001,4(4):22-26.
[24] Altiparmak F, Gen M, Lin L, et al. A Steady-state Genetic Algorithm forMulti-product Supply Chain Network Design [J]. Computers&IndustrialEngineering,2009(56):521-537.
[25]金海河,陈剑.分销配送网络优化模型及求解算法[J].清华大学学报,2002,42(6):739-742.
[26]谭凌,高峻峻,王迎军.基于库存成本优化的配送中心选址问题研究[J].系统工程学报,2004,19(1):59~65.
[27] Melo M T, Nickel S, Saldanha-da-Gama F. Dynamic Multi-commodityCapacitated Facility Location: A Mathematical Modeling Framework forStrategic Supply Chain Planning [J]. Computers and Operations Research,2006(33):181-208.
[28] Dias J, Captivo M E, Climaco J. Capacitated Dynamic Location Problemswith Opening, Closure and Reopening of Facilities [J]. IMA Journal ofManagement Mathematics,2006(17):317-348.
[29] Thanha P N, Bostelb N, Péton O. A Dynamic Model for Facility Location inthe Design of Complex Supply Chains [J]. International Journal ofProduction Economics,2008(113):678-693.
[30] Melachrinoudis E, Min H. The Dynamic Relocation and Phase-out of aHybrid, Two-echelon Plant/Warehousing Facility: A Multiple ObjectiveApproach [J]. European Journal of Operational Research,2000(123):1-15.
[31]翟恩东,汪定伟.考虑库存分配的多年度二级分销网络优化模型[J].东北大学学报,2001,22(2):175-178.
[32]狄卫民,胡培.制造/在制造物流网络优化设计的多周期静态选址模型[J].中国机械工程,2008,19(16):1950-1954.
[33]税文兵,叶怀珍,张诗波.物流配送中心动态选址模型及算法研究[J].计算机应用研究,2010,27(12):4476-4479.
[34] Vorst J, Tromp S, and Zee D. A Simulation Environment for the Redesign ofFood Supply Chain Networks Modeling Quality Controlled Logistics [C].Proceedings of the37th Conference on Winter Simulation, Orlando, FL,2005:1658-1667.
[35] Farahani R Z, Elahipanah M. A Genetic Algorithm to Optimize the TotalCost and Service Level for Just-in-time Distribution in a Supply Chain [J].International Journal of Production Economics,2008(111):229-243.
[36] Melachrinoudis E, Min H. Redesigning a Warehouse Network [J]. EuropeanJournal of Operational Research,2007(176):210-229.
[37] Kaplan U, Türkay M, Karas zen B, Biegler LT. Optimization of SupplyChain Systems with Price Elasticity of Demand [J]. Informs journal oncomputing,2011,23:557–568.
[38] Harris F W. How Many Parts to Make at Once [J]. The Magazine ofManagement,1913,10(2):135-136.
[39] Whitin T M. Inventory Control and Price Theory [J]. Management Science,1995,2(1):61-80.
[40] Clark A J, Scarf H. Oprtinal Policies of a Multi-eshelon Inventory Problem[J]. Management Science,1960,6(4):475-490.
[41] Graves S C. A Multi-echelon Inventory Model with Fixed ReplenishmentIntervals [J]. Management Science,1996,42(1):1-18.
[42] Chen F, Zheng Y S. One Warehouse Multi-retailer Systems with CentralizedStock Information [J]. Operations Research,1997(45):275-287.
[43] Dong L, Lee H L. Optimal Policies and Approximations for a SerialMultiechelon Inventory System with Time-correlated Demand [J].Operations Research,2003,51(6):96-99.
[44] Chel K P, Niel U. Simulation-based Optimization of Multi-echlon InventorySystems [J]. International Journal of Production Economics,2005(93-94):505-51.
[45]张钦,沈厚才,达庆利.供应链管理：两级分销系统的最优订货策略[J].系统工程学报,2002,17(4):303-308.
[46]高峻峻,王迎军,郭亚军.需求不确定的分销系统最小成本模型[J].东北大学学报,2002,23(1):87-90.
[47]卫忠,徐晓飞,战德臣,等.协同供应链多极库存控制的多目标优化模型及求解方法[J].自动化学报,2007,33(2):181-187.
[48]胡建国,冯恩民,郭华.随机需求条件下分销系统协同库存策略研究[J].大连理工大学学报,2009,49(2):288-293.
[49]王正元,宋建社,何志德,等.一种备件多极库存系统的仿真优化模型[J].系统仿真学报,2007,19(5):1003-1006.
[50] Hariga M. An EOQ Lot Sizing Model with Random Supplier Capacity [J].International Journal of Production Economics,1999(59):39-47.
[51] Zipkin P H. Foundations of Inventory Management [M]. Boston:McGraw-Hill,2000.
[52]郭强.对具有库存损耗的EOQ模型的研究[J].系统工程,2004,22(7):17-19.
[53]柏庆国,张玉忠,徐健腾.易变质产品在带运输时间的二级供应链中的订购策略研究[J].管理学报,2011,8(2):294-300.
[54] Ritchie E. Practical Inventory Replenishment Policies for a Linear TrendDemand [J]. Journal of Operational Research Society,1980(33):605-613.
[55] Wee H M. Economic Production Lot Size Model for Deterioration Items withPartial Backordering [J]. Computers and Industrial Engineering,1993,(24):449-458.
[56]罗兵,黄波,卢娜.一种线性时变需求且短缺量部分拖后的VMI模型[J].系统工程理论与实践,2006,26(5):36-41.
[57]张捍东,王青云,岑豫皖.弹性需求条件下具有库存损耗的经济订货批量模型[J].计算机集成制造系统,2009,15(8):1528-1533.
[58] Moon I, Gallego G. Distribution Free Procedures for Some Inventory Models[J]. The Journal of the Operational Research Society,1994,45(6):651-658.
[59] Andersson J, Axs ter S, Marklund J. Decentralized Multi-echelon InventoryControl [J]. Production and Operations Management,1998(7):370-386.
[60] Axs ter S. A Framework for Decentralized Multi-echelon Inventory Control[J]. IIE Transactions,2001,33:91-97.
[61] Strijbosch L W G, Moors J J A. The Impact of Unknown Demand Parameterson (R, S) Inventory Control Performance [J]. European Journal ofOperational Research,2005,162(1):805-815.
[62] Wensing T. Periodic Review Inventory Systems [M]. New York: Springer,2011.
[63]马士华,林勇.基于随机提前期的（Q,r）库存模型[J].计算机集成制造系统,2002,8(5):396-398.
[64]高峻峻,王迎军,郭亚军,等.一类随机需求下分销系统的主从对策模型即仿真[J].系统管理学报,2007,16(3):230-236.
[65]刘保政,汪定伟.连锁营销下随机需求的分销系统双层补货优化控制模型[J].控制与决策,2010,25(5):735-739.
[66] Veinott J A F. Optimal Policy in a Dynamic, Single Product, Non-stationaryInventory Model with Several Demand Classes [J]. Operations Research,1965(13):761–778.
[67] Topkis D M. Optimal Ordering and Rationing Policies in a Non-stationaryDynamic Inventory Model with n Demand Classes [J]. Management Science,1968(15):160-176.
[68] Frank K C, Zhang R Q, Duenyas I. Optimal Policies for Inventory Systemswith Priority Demand Classes [J]. Operations Research,2003,51(6):993-1002.
[69] Sen A, Zhang A X. The Newsboy Problem with Multiple Demand Classes [J].IIE T ransaction,1999(31):431-444.
[70] Ding Q, Kouvelis P, Milner J M. Dynamic Pricing through Discounts forOptimizing Multiple-class Demand Fulfillment [J]. Operations Research,2006(1):169-183.
[71] Ding Q, Kouvelis P, Milner J M. Dynamic Pricing for Multiple ClassDeterministic Demand Fulfillment [J]. IIE Transactions,2007(39):997-1013.
[72]裘民民,赵晓波,王建才.基于(s,S)库存策略的分销系统最优分配问题[J].清华大学学报(自然科学版),2006,46(5):749-752.
[73]汪达钦,霍佳震.有限时域下多需求类型产品的库存策略[J].系统工程理论与实践,2010,30(6):981-986.
[74]汪小京,刘志学,郑长征.多类顾客环境下报童模型中库存分配策略研究[J].中国管理科学,2010,18(4):65-72.
[75]汪小京,刘志学,郑长征.周期性补货系统中多类顾客的库存分配策略[J].武汉理工大学学报,2010,32(4):661-667.
[76] Nahmias S, Demmy S. Operating Characteristics of an Inventory Systemwith Rationing [J]. Management Science,1981(27):1236–1245.
[77] Moon I, Kang S. Rationing Policies for Some Inventory Systems [J]. Journalof Operation Research Socioty,1998(49):509-518.
[78] Dekker R, Kleijn M J, Rooij P J. A Spare Parts Stocking System based onEquipment Criticality [J]. International Journal of Production Economics,1998,56(7):69-77.
[79] Ha A Y. Inventory Rationing in a Make-to-Stock Production System withSeveral Demand Classes and Kost Sales [J]. Management Science,2000,43(8):1093-1103.
[80] Melchiors P, Dekker R, Kleijn M. Inventory Rationing in an (s, Q) InventoryModel with Lost Sales and Two Demand Classes [J]. Journal of OperationResearch Socioty,2000,51(1):11–122.
[81] Sapna I K P. An (S,Q) Markovian Inventory System with Lost Sales and TwoDemand Classes [J]. Mathematical and Computer Modelling,2006(43):687-694.
[82]刘文丽,王欣宇.代发货环境下网络销售商的阈值库存分配策略[J].系统工程学报,2008,23(6):650-658.
[83]周伟华,吴晓波,杜健.服务多类需求串行供应链的最优控制策略[J].管理科学学报,2010,13(3):19-28.
[84] Laporte G. Fifty Years of Vehicle Routing [J]. Transportation Science,2009(43):408-416.
[85] Mendoza J E, Casranier B, Guéret C, et al. A Memetic Algorithm for theMulti-compartment Vehicle Routing Problem with Stochastic Demands [J].Computers&Operations Research,2010(37):1886-1898.
[86] Thomas D J, Griffin P M. Coordinated Supply Chain Management [J].European Journal of Operational Research,1996(94):1-15.
[87]熊峰.供应链协同调度研究[D].武汉:武汉理工大学博士学位论文,2009.
[88]姚珣.不确定性下的供应链协调机制及其应急管理研究[D].成都:电子科技大学,2009.
[89] Rathi A K, Church R L, Solanki R S. Allocation Resources to Support aMulti Commodity Flow with Time Windows [J]. Logisitics andTransportation Review,1993(28):167-188.
[90] Equi L, Gallo G, Marziale S, et al. A Combined Transportation andScheduling Problem [J]. European Joumal of Operational Research,1997(97):94-104.
[91] Hong S C, Park Y B. A Heuristic for Bi-objective Vehicle Routing with TimeWindow Constraints [J]. International Journal of Production Economics,1999(62):249-258.
[92] Yang S, Hamedi M, Haghani A. Online Dispatching and Routing Model forEmergency Vehicles with Area Coverage Constraints [J]. TransportationResearch Record: Journal of the Transportation Research Board,2005(1923):1-8.
[93]任文君,孙利辉,李霞.基于缺货损失的配送中心调度在线策略[J].系统工程,2010,28(10):114-117.
[94] Li L, Lee Y. Pricing and Delivery-time Performance in a CompetitiveEnvironment [J]. Management Science,1994,40(5):633-646.
[95] Palaka K, Erlebacher S, Kropp D H. Lead Time Setting, Capacity Utilization,and Pricing Decisions under Lead Time Dependent Demand [J]. IIETransactions,1998(30):151-163.
[96] Ernst R, Kamrad B. Allocation of Warehouse Inventory with Electronic DataInterchanges and Fixed Order Intervals [J]. European Journal of OperationalResearch,1997(103):117-128.
[97] Boyaci T, Ray S. Production Differentiation and Capacity Cost Interaction inTime and Price Sensitive Demand [J]. Manufacturing&Service OperationsManagement,2003(5):18-36.
[98] Qi X T, Bard J F, Yu G. Supply Chain Coordination with DemandDisruptions [J]. Omega,2004,32(4):301-312.
[99] Chan F T S, Chan H K. A Simulation Study with Quantity Flexibility in aSupply Chain Subjected to Uncertainties [J]. International Journal ofComputer Integrated Manufacturing,2006,19(2):148-160.
[100]于辉,陈剑,于刚.批发价契约下的供应链应对突发事件[J].系统工程理论与实践,2006,8(8):33-41.
[101]戢守峰,杜晓璐,黄小原.协同商务下分销系统紧急补货模型与分析[J].东北大学学报,2007,28(5):753-756.
[102] Axs ter S. Modeling Emergency Lateral Transshipments in InventorySystems [J]. Management Science,1990(36):1329-1338.
[103] Lee H L.A. Multi-echelon Inventory Model for Repairable Items withEmergency Lateral Transshipments [J]. Management Science,1987(33):1302-1316.
[104] Zhao H, Deshpande V. Inventory Sharing and Rationing IndecentralizedDealer Networks [J]. Management Science,2005,51(4):531–547.
[105] Herer Y T, Tzur M, Yucesan E. The Multilocation Transshipment Problem [J].IIE Transactions,2006(38):185–200.
[106]李怡娜,徐学军.双分销渠道下短生命周期产品供应链转运策略[J].计算机集成制造系统,2010,16(1):155-164.
[107] Tagaras G. Pooling in Multi-location Periodic Inventory DistributionSystems [J]. Omega,1999(27):39-59.
[108] Banerjee A, Burton J, Banerjee S. A Simulation Study of Lateral Shipmentsin Single Supplier, Multiple Buyers Supply Chain Networks[J]. InternationalJournal of Production Economics,2003(81–82):103–114.
[109]李晓宏,孙林岩,李刚.不确定性需求下易逝品销售商横向调货策略研究[J].运筹与管理,2009,18(5):76-80.
[110] Tiacci L, Saetta S. A Heuristic for Balancing the Inventory Level of DifferentLocations through Lateral Shipments [J]. International Journal of ProductionEconomics,2010,131(1):1-9.
[111]孙会君,高自友.基于双层规划的供应链二级分销网络优化设计模型[J].管理工程学报,2004,18(1):68-71.
[112]刘昱岗,郝光,罗霞.基于模糊多目标格序决策的分销网络优化模型[J].系统工程,2006,24(7):16-20.
[113]李良,康杰,喻伟.顾客选择行为与库存[J].系统工程,2003,21(1):86-89.
[114]刘蕾,唐小我.订货提前期对服务水平决策的影响研究[J].控制与决策,2005,20(11):1265-1268.
[115] Lee J K, Larry L P. Operations Management Strategy and Analysis [M]. NewJersey: Prentice Hall,2002.
[116] Yan H, Yu Z, Edwin Cheng T C. A Strategic Model for Supply Chain Designwith Logical Constraints: Formulation and Solution [J]. Computers andOperations Research,2003(30):2135-2155.
[117] Biswas S, Narahari Y. Object Oriented Modeling and Decision Support forSupply Chains [J]. European Journal of Operational Research,2004(153):704-726.
[118]马士华,林勇,陈志祥.供应链管理[M].北京:机械工业出版社,2000.
[119]徐晓飞,王忠杰,莫同.服务工程方法体系[J].计算机集成制造系统,2007,13(8):1457-1464.
[120]刘作仪,杜少甫.服务科学管理与工程:一个正在兴起的领域[J].管理学报,2008,5(4):607-615.
[121] Hill T P. On Goods and Services [J]. The Review of Income and Wealth.1997,23(4):315-338.
[122] IBM Research. Services Science, Management and Engineering-ServicesDefinition [EB/OL]. http://www. research. ibm. com/ssme/services. shtml.2008.
[123] M. Christopher.物流与供应链管理：降低成本与改善服务的战略（英文版）[M].北京:电子工业出版社,2003.
[124] Gr nroos C. Service Management: A Management Focus for ServiceCompetition [J]. International Journal of Service Industry Management,1990,1(1):6-14.
[125] Gadrey J. Productivity, Innovation and Knowledge in Services: NewEconomic and Socio-Economic Approaches [M]. Cheltenham, UK: EdwardElgar Publisher,2002.
[126]朱丹.供应链应急物流系统构建研究[J].北京交通大学学报.2011,10(2):59-64.
[127] Laporte G. Vehichle Routing: Methods and Studies [M]. Amsterdam:North-Holland,1998.
[128] Donald W F, John H B, Thomas R H. Production&Inventory Management[M]. Cincinnati, OH: South-Western Pub. Co.,1991.
[129] Zhou A, Qu B, Li H, Zhao S. Multiobjective evolutionary algorithms: Asurvey of the state of the art [J]. Swarm and Evolutionary Computation,2011(1):32–49.
[130] Saaty T L. Decision Making with Dependence and Feedback [M]. Pittsburgh,PA., USA: RWS Publication,1996.
[131] Zhang X, Wang C. Application of Analytic Network Process in AgriculturalProducts Logistics Performance Evaluation [J].Innovative Computing andInformation,2011(231):500-506.
[132] Amin S H, Zhang G. An Integrated Model for Closed-loop Supply ChainConfiguration and Supplier Selection: Multi-objective Approach [J]. ExpertSystems with Applications,2012,39(8):6782-6791.
[133] elebi D, Bayraktar D, Bing l L. Analytical Network Process for LogisticsManagement: A Case Study in a Small Electronic Appliances Manufacturer[J]. Computers&Industrial Engineering,2010,58(3):432-441.
[134] Ludmil M, Madan G S. Fuzzy Analytic Network Process and its Applicationto the Development of Decision Support Systems [J]. IEEE Transactions onSystems, Man, and Cybernetics-Part C: Applications and Reviews,2003,33(1):33-41.
[135] Cheng C H, Mon D L. Evaluating Weapon System by Analytical HierarchyProcess based on Fuzzy Scales [J]. Fuzzy Sets and Systems,1994(63):1-10.
[136] Hnaien F, Delorme X, Dolgui A. Multi-objective Optimization for InventoryControl in Two-level Assembly Systems under Uncertainty of Lead Times [J].Computer and Operations Research,2010(37):1835-1843.
[137] Ko H, and Evans G. A Genetic Algorithm-based Heuristic for the DynamicIntegrated Forward/Reverse Logistics Network for3pls [J]. Computers andOperations Research,2007(34):346–366.
[138] Gen M, Cheng R. Genetic Algorithms and Engineering Optimization [M].New York: Wiley,2000.
[139] Prüfer H. Neuer Beweis Eines Satzes über Permutationen [J]. Archives ofMathematical Physics,1918(27):142-144.
[140] Syarif A, Yun Y S, Gen M. Study on Multi-stage Logistic Chain Network: ASpanning Tree-based Genetic Algorithm Approach [J].Computers&Industrial Engineering,2002(43):299-314.
[141] Gen M, Kumar A, Kim J R. Recent Network Design Techniques usingEvolutionary Algorithms [J]. International Journal of Production Economics,2005(98):251-261.
[142] Krishnamoorthy M, Ernst A T, Sharaiha Y M. Comparison of Algorithms forthe Degree Constrained Minimum Spanning Tree [J]. Journal of Heuristics,2001(7):587-611.
[143] Yeh W C. Ahybrid Heuristic Algorithm for the Multistage Supply ChainNetwork Problem [J]. Internal Journal of Advanced ManufacturingTechnology,2005(26):675-685.
[144] Abuali F N, Wainwright R L, Schoenefeld D A. Determinant Factorization: ANew Encoding Scheme for Spanning Trees Applied to the ProbabilisticMinimum Spanning Tree Problem [C]. Proceedings of the Sixth InternationalConference on Genetic Algorithms, SanMateo, CA: Morgan Kaufmann,1995:470-477.
[145] Chou H, Premkumar G, Chu C H. Genetic Algorithm for CommunicationsNetwork Design: an Empirical Study for the Factors that InfluencePerformance [J]. IEEE Transactions on Evolutionary Computation,2001,5(3):236-249.
[146] Yao M J, Hsu H W. A New Spanning Tree-based Genetic Algorithm for theDesign of Multi-stage Supply Chain Network with Nonlinear TransportationCosts [J]. Optimizationand Engineering,2009,10(2):219-37.
[147] Wang H F, Hsu H W. A Closed-loop Logistic Model with a Spanning-treebased Genetic Algorithm [J]. Computers&Operations Research,2010(37):376-389.
[148]蒋绍忠.管理运筹学教程[M].杭州:浙江大学出版社,2005:292-319.
[149] Boch G, Greiner S. Queueing Networks and Markov Chains Modeling andPerformance Evaluation with Computer Science Applications [M]. NewJersey: John Wiley&Sons, Inc,2006.
[150] Gembicki F W, Haimes Y Y. Approach to Performance and SensitivityMulti-objective Optimization: the Goal Attainment Method [J]. IEEETransactions on Automatic Control,1975,20(6):769–771.
[151] Charnes A, Cooper W W, Ferguson R. Optimal Estimation of ExecutiveCompensation by Linear Programming [J]. Management Science,1955,1(2):138-151.
[152] Goh C K, Ong Y S, and Tan K C. Multi-Objective Memetic Algorithms [M].New York: Springer,2010.
[153] Yeh W C. An Efficient Memetic Algorithm for the Multi-stage Supply ChainNetwork Problem [J]. International Journal of Advanced ManufacturingTechnology,2005,29(7-8):803-813.
[154] Boudia M, Prins C. A Memetic Algorithm with Dynamic PopulationManagement for an Integrated Production–distribution Problem [J].European Journal of Operational Research,2009(195):703–15.
[155] ElMekkawy T Y, Liu S. A New Memetic Algorithm for Optimizing thePartitioning Problem of Tandem AGV Systems [J]. International Journal ofProduction Economics,2009,118(2):508–20.
[156] Joana D, Captivo M E, Clímaco J. A Memetic Algorithm for Multi-objectiveDynamic Location Problems [J]. Journal of Global Optimization,2008(42):221–253.
[157] Gen M, Altiparmak F, Lin L. Agenetic Algorithm for Two-stageTransportation Problem using Priority-based Encoding [J]. OR Spectrum,2006,28(7):337-354.
[158] Ishibuchi H, Murata T. A Multiobjective Genetic Local Search Algorithmand Its Application to Flowshop Scheduling [J]. IEEE Transactions onSystems, Man and Cybernetics,1998,28(3):392–403.
[159] Bertsimas D J, Chervi P, Peterson M. Computational Approaches toStochastic Vehicle Routing Problems [J]. Transportation Science,1995,29(4):342–352.
[160] Ishibuchi H, Yoshida T, Murata T. Balance between Genetic Search andLocal Search in Memetic Algorithms for Multi objective Permutation Flowshop Scheduling [J]. IEEE Transactions on Evolutionary Computation,2003,7(2):204-223.
[161] Knowles J, Corne D. A Memetic Algorithm for Multiobjective Optimization[C]. Proceedings of the Congress on Evolutionary Computation, New Jersey,2000:325-332.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |