基于多智能体理论的汽车逆向物流库存控制理论与方法研究
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摘要
汽车回收是一个很大的产业,资源潜力巨大,经济效益显著。加强废旧汽车的回收利用,可以实现资源的循环利用,推动汽车行业的可持续发展。我国的汽车保有量和报废汽车数量都在逐年增加,因此,实施和加强汽车逆向物流对于我国来说具有重要的战略意义。
在汽车逆向物流研究领域中,库存控制是其重要的研究内容之一,良好的库存控制可以加快企业资金使用效率、周转速度、增加投资收益,可以提高逆向物流系统的效率、增强企业的竞争力。然而,汽车逆向物流库存控制系统是一个复杂的非线性时变系统,具有复杂系统的不确定性、动态性、数据量庞大等特点。针对这一复杂系统,本文引入多智能体理论(MAS),对汽车逆向物流库存控制问题进行研究。多智能体系统是一种崭新且应用前景广阔的研究方法,是更接近自然界本身解题方式的研究方法,具有良好的鲁棒性和灵活性,非常适合处理知识、数据、资源、控制分布的问题。多智能体系统强调分布式自主决策,强调各个Agent之间协作解决问题的能力,这些特点正好契合于汽车逆向物流库存控制在实际运行中所表现出来的动态性、自治性、分布性、弱耦合性等特征。
本文首先研究了逆向物流、库存控制以及逆向物流中库存控制等理论,在此基础上,分析了汽车逆向物流的内容、参与主体和逆向物流网络以及汽车逆向物流库存控制系统的特点、要素和不确定因素,论述了汽车逆向物流和汽车逆向物流库存控制系统的复杂性,为基于多智能体理论的汽车逆向物流库存控制研究提供依据。
其次,从整个供应链的角度进行逆向物流库存控制的分析和研究,包含供应商、制造商、销售商、回收中心等环节。针对以汽车制造商为中心的供应链多级库存控制问题,提出并建立了汽车逆向物流多级库存控制模型,对可销售产品库存主导的控制模型和回收产品库存主导的控制模型分别建立了汽车逆向物流定期检查处理和定量检查处理的库存控制模型。
第三,对Agent技术和多智能体理论进行了详细分析研究,在此基础上,建立了基于多智能体理论的汽车逆向物流库存控制系统模型,并对各Agent进行角色划分,使其更加适合汽车逆向物流库存控制系统,同时,对Agent间的通信和协作方法进行了研究,提出了适合汽车逆向物流库存控制系统的Agent间的通信方式和通信机制,以及Agent间的协作方法。
第四,针对某汽车发动机制造企业为中心的逆向物流供应链库存实际进行了实证研究,对库存控制分别进行了建模、仿真计算、灵敏度分析和协作性分析。仿真结果证明了所建立的两种库存控制模型和所采用的基于多智能体理论的库存控制能有效降低汽车逆向物流库存成本。灵敏度分析证明了产品的回收率和回收产品的可再制造率对制造商和回收中心的生产和库存都有很大的影响,提高产品回收率和回收产品的再制造率在一定程度上可以减少逆向物流的库存成本。对两种库存控制模型的协作性分析结果是：各成员企业间存在协作与不存在协作和仅仅制造商和回收中心间存在协作相比,总库存成本分别减少了9.8%和6.5%,12.4%和6.5%。协作性分析证明了通过协调供应链上各成员企业间的库存控制策略可以使整个供应链库存控制达到协调性和一致性,从而降低供应链的库存成本。
第五,针对汽车逆向物流库存控制系统,本文提出并建立了相应的绩效评价体系和绩效评价方法,对汽车逆向物流库存控制系统运作所产生的效果进行度量和评价,对汽车逆向物流供应链的整体运行绩效以及各成员企业间的合作关系做出评价,以判断汽车逆向物流库存控制的运作绩效,为寻求更有效的库存控制方式提供评价依据。
最后,从制造商、回收中心和回收商,以及整个物流系统考虑,针对如何降低逆向物流系统的库存成本,提出了控制库存成本、提高库存协调性的策略。
本文主要是针对汽车逆向物流库存控制问题进行研究,创新引入了多智能体理论,提出了基于多智能体理论的汽车逆向物流库存控制理论和方法,力求达到优化库存成本,避免需求损失和利润损失,更好地管理整个逆向物流系统,促进资源循环利用的目的。论文针对某汽车发动机制造企业为中心的逆向物流供应链库存实际,进行了实证分析,为我国汽车逆向物流库存控制提供了理论基础与技术保障。
Automobile recycling is a big industry with enormous resource and significant economic benefits. The recycling of the waste automobiles can realize the resource recycling and promote the development of the automobile industry. The car ownership and the number of the waste cars in China are increasing year by year, therefore, it has an important strategic significance to our country that implementing and strengthening the automobile reverse logistics.
In the automobile reverse logistics research field, stock control is an important one. Good stock control can increase the efficiency, velocity and investment income of enterprise fund, which can improve the efficiency of reverse logistics system, and enhance the competitiveness of the company. However, automobile reverse logistics stock control is complex, nonlinear, time-varying, having the characteristics of uncertainty, dynamics and large amounts of data. To deal with it, multi-agent theory is introduced to study automobile reverse logistics stock control in the text. MAS is a novel and prospective method, more close to the way the nature solves problem itself. With good robustness and flexibility, it's good at dealing with knowledge, data, resources and control distribution. MAS emphasizes distributed independent decision-making and the ability of problem solving through the agents corporate with each other. These qualities correspond to the characteristic the automobile reverse logistics stock control shows in actual operation as dynamics, self-governing, distribution, and weak coupling.
Firstly, on the base of the study on the theory of the reverse logistics, inventory control and the inventory control of the reverse logistics, the content, the main participating part and the reverse logistics network of the automobile reverse logistics, as well as the characteristics, key elements and the uncertain factors of the automobile reverse logistics inventory control system are analyzed. Meanwhile, to provide the basis for the study on the automobile reverse logistics inventory control based on multi agent theory, the complexity of automobile reverse logistics and the automobile reverse logistics inventory control system are discussed.
Secondly, reverse logistics inventory control is analyzed and studied from the perspective of the entire supply chain, including suppliers, manufacturers, vendors, recycling centers and other sectors. A multi-level car reverse logistics inventory control model is built for the problem of multi-level inventory control of supply chain where the automobile manufacturers are the center. Inventory control models for periodically check process and quantitative examination process are built for the control models where salable product inventory and recovery product inventory play a leading part respectively.
Thirdly, Agent technology and multi-agent theory are analyzed in detail. On this basis, a car reverse logistics inventory control system model based on multi-agent theory is established. In addition, the methods of communication and collaboration between the Agents are studied to determine the means and mechanisms of communication as well as collaborative approach among Agents.
Fourthly, the Swarm simulation platform can be used to execute instance simulation, sensitivity analysis and collaborative analysis, which is based on the control problems of reverse logistics supply chain inventory centering a car engine manufacturing enterprise. The simulation results prove that the two established inventory control models and the multi-agent theory can effectively reduce the inventory cost of automobile reverse logistics. Besides, the sensitivity analysis certifies that the products recovery and remanufacturing have a great influence on the manufacturers, as well as the production and inventory of recycling centers. The cost of reverse logistics inventory can be reduced to a certain extent along with the improvement of products recovery and remanufacturing. What's more, the collaborative analysis results of the two inventory control models show that compared to the total inventory cost when there is coordination only between manufacturers and recycling center, it decreased by11.8%and6.5%for one model,12.4%and6.5%for another one according to whether coordination exists between each node enterprise. Collaborative analysis demonstrate that coordinating the supply chain inventory control strategy of each node enterprises can help the whole supply chain inventory control achieve coordination and coherence, thus reducing inventory cost of the supply chain.
Fifthly, in view of the automobile reverse logistics control system, performance evaluation system is established to measure and evaluate the effect of the inventory control system. It can judge the operation performances of automobile reverse inventory control, as well as providing the basis of the evaluation for seeking more effective inventory control method.
Finally, in terms of the manufacturer, the recycling center, recyclers as well as the whole logistics system, a strategy aiming at reducing the inventory cost of reverse logistics system is put forward to control inventory cost and improve inventory coordination.
The problem studied in this paper is mainly about the control of automobile reverse logistics inventory. To reach the purpose of making efforts to achieve optimal inventory costs, avoiding the demand and profit loss, better managing the whole reverse logistics system, promoting the resources recycling, it innovatively introduce multi-agent theory which provides theoretical basis and technical support for China's automobile reverse logistics inventory control.
在汽车逆向物流研究领域中,库存控制是其重要的研究内容之一,良好的库存控制可以加快企业资金使用效率、周转速度、增加投资收益,可以提高逆向物流系统的效率、增强企业的竞争力。然而,汽车逆向物流库存控制系统是一个复杂的非线性时变系统,具有复杂系统的不确定性、动态性、数据量庞大等特点。针对这一复杂系统,本文引入多智能体理论(MAS),对汽车逆向物流库存控制问题进行研究。多智能体系统是一种崭新且应用前景广阔的研究方法,是更接近自然界本身解题方式的研究方法,具有良好的鲁棒性和灵活性,非常适合处理知识、数据、资源、控制分布的问题。多智能体系统强调分布式自主决策,强调各个Agent之间协作解决问题的能力,这些特点正好契合于汽车逆向物流库存控制在实际运行中所表现出来的动态性、自治性、分布性、弱耦合性等特征。
本文首先研究了逆向物流、库存控制以及逆向物流中库存控制等理论,在此基础上,分析了汽车逆向物流的内容、参与主体和逆向物流网络以及汽车逆向物流库存控制系统的特点、要素和不确定因素,论述了汽车逆向物流和汽车逆向物流库存控制系统的复杂性,为基于多智能体理论的汽车逆向物流库存控制研究提供依据。
其次,从整个供应链的角度进行逆向物流库存控制的分析和研究,包含供应商、制造商、销售商、回收中心等环节。针对以汽车制造商为中心的供应链多级库存控制问题,提出并建立了汽车逆向物流多级库存控制模型,对可销售产品库存主导的控制模型和回收产品库存主导的控制模型分别建立了汽车逆向物流定期检查处理和定量检查处理的库存控制模型。
第三,对Agent技术和多智能体理论进行了详细分析研究,在此基础上,建立了基于多智能体理论的汽车逆向物流库存控制系统模型,并对各Agent进行角色划分,使其更加适合汽车逆向物流库存控制系统,同时,对Agent间的通信和协作方法进行了研究,提出了适合汽车逆向物流库存控制系统的Agent间的通信方式和通信机制,以及Agent间的协作方法。
第四,针对某汽车发动机制造企业为中心的逆向物流供应链库存实际进行了实证研究,对库存控制分别进行了建模、仿真计算、灵敏度分析和协作性分析。仿真结果证明了所建立的两种库存控制模型和所采用的基于多智能体理论的库存控制能有效降低汽车逆向物流库存成本。灵敏度分析证明了产品的回收率和回收产品的可再制造率对制造商和回收中心的生产和库存都有很大的影响,提高产品回收率和回收产品的再制造率在一定程度上可以减少逆向物流的库存成本。对两种库存控制模型的协作性分析结果是：各成员企业间存在协作与不存在协作和仅仅制造商和回收中心间存在协作相比,总库存成本分别减少了9.8%和6.5%,12.4%和6.5%。协作性分析证明了通过协调供应链上各成员企业间的库存控制策略可以使整个供应链库存控制达到协调性和一致性,从而降低供应链的库存成本。
第五,针对汽车逆向物流库存控制系统,本文提出并建立了相应的绩效评价体系和绩效评价方法,对汽车逆向物流库存控制系统运作所产生的效果进行度量和评价,对汽车逆向物流供应链的整体运行绩效以及各成员企业间的合作关系做出评价,以判断汽车逆向物流库存控制的运作绩效,为寻求更有效的库存控制方式提供评价依据。
最后,从制造商、回收中心和回收商,以及整个物流系统考虑,针对如何降低逆向物流系统的库存成本,提出了控制库存成本、提高库存协调性的策略。
本文主要是针对汽车逆向物流库存控制问题进行研究,创新引入了多智能体理论,提出了基于多智能体理论的汽车逆向物流库存控制理论和方法,力求达到优化库存成本,避免需求损失和利润损失,更好地管理整个逆向物流系统,促进资源循环利用的目的。论文针对某汽车发动机制造企业为中心的逆向物流供应链库存实际,进行了实证分析,为我国汽车逆向物流库存控制提供了理论基础与技术保障。
Automobile recycling is a big industry with enormous resource and significant economic benefits. The recycling of the waste automobiles can realize the resource recycling and promote the development of the automobile industry. The car ownership and the number of the waste cars in China are increasing year by year, therefore, it has an important strategic significance to our country that implementing and strengthening the automobile reverse logistics.
In the automobile reverse logistics research field, stock control is an important one. Good stock control can increase the efficiency, velocity and investment income of enterprise fund, which can improve the efficiency of reverse logistics system, and enhance the competitiveness of the company. However, automobile reverse logistics stock control is complex, nonlinear, time-varying, having the characteristics of uncertainty, dynamics and large amounts of data. To deal with it, multi-agent theory is introduced to study automobile reverse logistics stock control in the text. MAS is a novel and prospective method, more close to the way the nature solves problem itself. With good robustness and flexibility, it's good at dealing with knowledge, data, resources and control distribution. MAS emphasizes distributed independent decision-making and the ability of problem solving through the agents corporate with each other. These qualities correspond to the characteristic the automobile reverse logistics stock control shows in actual operation as dynamics, self-governing, distribution, and weak coupling.
Firstly, on the base of the study on the theory of the reverse logistics, inventory control and the inventory control of the reverse logistics, the content, the main participating part and the reverse logistics network of the automobile reverse logistics, as well as the characteristics, key elements and the uncertain factors of the automobile reverse logistics inventory control system are analyzed. Meanwhile, to provide the basis for the study on the automobile reverse logistics inventory control based on multi agent theory, the complexity of automobile reverse logistics and the automobile reverse logistics inventory control system are discussed.
Secondly, reverse logistics inventory control is analyzed and studied from the perspective of the entire supply chain, including suppliers, manufacturers, vendors, recycling centers and other sectors. A multi-level car reverse logistics inventory control model is built for the problem of multi-level inventory control of supply chain where the automobile manufacturers are the center. Inventory control models for periodically check process and quantitative examination process are built for the control models where salable product inventory and recovery product inventory play a leading part respectively.
Thirdly, Agent technology and multi-agent theory are analyzed in detail. On this basis, a car reverse logistics inventory control system model based on multi-agent theory is established. In addition, the methods of communication and collaboration between the Agents are studied to determine the means and mechanisms of communication as well as collaborative approach among Agents.
Fourthly, the Swarm simulation platform can be used to execute instance simulation, sensitivity analysis and collaborative analysis, which is based on the control problems of reverse logistics supply chain inventory centering a car engine manufacturing enterprise. The simulation results prove that the two established inventory control models and the multi-agent theory can effectively reduce the inventory cost of automobile reverse logistics. Besides, the sensitivity analysis certifies that the products recovery and remanufacturing have a great influence on the manufacturers, as well as the production and inventory of recycling centers. The cost of reverse logistics inventory can be reduced to a certain extent along with the improvement of products recovery and remanufacturing. What's more, the collaborative analysis results of the two inventory control models show that compared to the total inventory cost when there is coordination only between manufacturers and recycling center, it decreased by11.8%and6.5%for one model,12.4%and6.5%for another one according to whether coordination exists between each node enterprise. Collaborative analysis demonstrate that coordinating the supply chain inventory control strategy of each node enterprises can help the whole supply chain inventory control achieve coordination and coherence, thus reducing inventory cost of the supply chain.
Fifthly, in view of the automobile reverse logistics control system, performance evaluation system is established to measure and evaluate the effect of the inventory control system. It can judge the operation performances of automobile reverse inventory control, as well as providing the basis of the evaluation for seeking more effective inventory control method.
Finally, in terms of the manufacturer, the recycling center, recyclers as well as the whole logistics system, a strategy aiming at reducing the inventory cost of reverse logistics system is put forward to control inventory cost and improve inventory coordination.
The problem studied in this paper is mainly about the control of automobile reverse logistics inventory. To reach the purpose of making efforts to achieve optimal inventory costs, avoiding the demand and profit loss, better managing the whole reverse logistics system, promoting the resources recycling, it innovatively introduce multi-agent theory which provides theoretical basis and technical support for China's automobile reverse logistics inventory control.
引文
[1]王长琼.绿色物流[M].北京：化学工业出版社,2004.
[2]李正锋.基于SWOT矩阵评析我国汽车企业逆向物流[J].华东经济治理,2007：61-63.
[3]阮略成,李杰.第三方汽车逆向物流模式浅析[J].汽车工业研究,2006：39-41.
[4]Laan E., Dekker R., Salomon M. Product Remanufacturing and Disposal:A Numerical Comparison of Alternative Strategies[J]. International Journal of Production Economics.1996,45.489-498.
[5]Schardy D A. A Deterministic Inventory Model for Repairable Items[J]. Naval Research Logistics Quarterly,1967,14:391-398.
[6]Mabini M C, Pintelon L M, Gelders L F. EOQ type formulations for controlling repairable inventories[J]. International Journal of Production Economics,1992,28:21-23.
[7]Richter K. The EOQ Repair and Waste Disposal Model with Variable Setup Numbers [J]. European Journal of Operational Research,1996,95:313-324.
[8]Richter K. The Extended EOQ Repair and Waste Disposal Model[J]. International Journal of Production Economics,1996,45:443-448.
[9]Teunter R.H.. Economic ordering quantities for recoverable item inventory systems [J]. Naval Research Logistics,2001,48:484-495.
[10]Minner S. Strategic safety stocks in reverse logistics supply chains[J]. International Journal of Production Economics,2001,71(3):417-428.
[11]Kleber R, Minner S, Kiesmuller G. A Continuous Time Inventory Model for a Product Recovery System with Multiple Options[J]. International Journal of Production Economics, 2002,79:121-141.
[12]Dobos I. Optimal Production-inventory Strategies for a HMMS-type Reverse Logistics System[J]. International Journal of Production Economics,2003,81-82:351-360.
[13]Kiesmuller G, Minner S. Simple expressions for finding recovery system inventory control parameter values[J]. Journal of the Operational Research Society.2003,54:83-88.
[14]Simpson V.P. Optimum solution structure for a repairable inventory problem[J]. Operations Research,1978,26 (2):270-281.
[15]Indefurth K. Simple optimal replenishment and disposal policies for product recovery system with lead times[J]. OR Spectrum,1997,19(2):111-222.
[16]Cohen MA, Nahmias S, Pierskalla W. A dynamic inventory system with recycling[J]. Naval Research Logistics Quarterly,1980,27(2):89-96.
[17]Kelle P, Silver E A. Purchasing policy of new containers considering the random returns of previously issued containers[J]. IIE Transactions,1989,21 (4):349-354.
[18]Buchanan D.J., Abad P. L. Optimal policy for a periodic review returnable inventory system[J]. IIE Transactions,1998,30:1049-1055.
[19]Toktay LB, Wein M, Zenios SA. Inventory management of remanufacturable products[J]. Management Science,2000,46(11):1412-1426.
[20]Kiesmuller G, Laan E.A., van der. An inventory model with dependent product demands and returns[J]. International Journal of Production Economics,2001,72:73-87.
[21]Teunter R.H., Vlachos D. On the necessity of a disposal option for returned items that can be remanufactured[J]. International Journal of Production Economics,2002,75:257-266.
[22]Mahadevan B, Pyke D.F., Fleischmann M. Periodic review, push inventory policies for remanufacturing[J]. European Journal of Operational Research,2003,151 (3):536-551.
[23]Mostard J, Koster R.D., Teunter R. The distribution-free newsboy problem with resalable returns[J]. International Journal of Production Economics,2003,97 (3):329-342.
[24]Vlachos D, Dekker R. Return handling options and order quantities for single period products[J]. European Journal of Operational Research,2003,151 (1):38-52.
[25]Adel A. Alamri. Theory and methodology on the global optimal solution to a GeneralReverse Logistics Inventory Model for deteriorating items andtime-varying rates[J]. Computers & Industrial Engineering,2011,60(2):236-247.
[26]Heyman D.P. Optimal disposal policies for a single-item inventory system with returns[J]. Naval Research Logistics Quarterly,1977,24:385-405.
[27]Muckstadt JA, Isaac MH. An analysis of single item inventory systems with returns[J]. Naval Research Logistics Quarterly,1981,28(2):37-54.
[28]Van D L E, Dekker R, Salomon M. An(s, Q)inventory model with remanufacturing and disposal [J]. International Journal of Production Economics,1996,46-47(3):339-350.
[29]Yuan X.M, Cheung K.L.. Modeling returns of merchandise in an inventory system[J]. OR Spectrum,1998,20 (3):147-154.
[30]Fleischmann M, Kuik R, Dekker R. Controlling Inventories with Stochastic Item Returns: a Basic Model[J]. European Journal of Operational Research,2002,138:63-75.
[31]Ahmed M.A. El Saadany. Mohamad Y. Jaber. A production/remanufacturing inventory model with price and quality dependant return rate[J]. Computers & Industrial Engineering, 2010:352-362.
[32]黄祖庆,达庆利.一个允许退货的库存控制策略模型[J].东南大学学报(自然科学版),2003,33(6)：792-795.
[33]陈秋双,刘东红.再制造系统的库存控制研究[J].南开大学学报(自然科学版),2003,36(3)：67-72.
[34]姚卫新.再制造条件下逆向物流回收模式的研究[J].管理科学,2004,17(1)：76-80
[35]黄祖庆,达庆利,王冬冬.逆向物流具有时滞的一个EOQ扩展订货模型[J].物流技术,2004,(5)：82-84.
[36]侯云章,戴更新,于庆东.二次订货策略在单周期产品逆向供应链中应用[J].系统工程理论与实践,2005,25(11)：35-40.
[37]杨杰,周磊山,孟翀,刘佳.包含逆向物流的供应链库存控制问题研究[J].北京交通大学学报,2006,(2)：15-18.
[38]李新军,达庆利.一种新型的再制造条件下EOQ模型[J].东南大学学报：自然科学版,2006,36(4)：667-671.
[39]黄祖庆,达庆利.基于逆向物流定期和定量处理的最优库存控制策略研究[J].东南大学学报(自然科学版),2005,35(2)：302-307.
[40]赵宜,蒲云,尹传忠.回收物流库存控制研究[J].中国管理科学,2005,13(5)：49-53.
[41]李常洪,石磊.一次逆向物流循环的库存控制模型探讨[J].物流技术,2009(10)：65-68.
[42]江玮璠,李文.基于蒙特卡罗的逆向物流库存控制研究[J].南吕工程学院学报,2010(3)：51-54.
[43]任鹏,邓书显.包含逆向物流的库存控制模型研究[J].西华大学学报(自然科学版),2010,29(4)：56-59.
[44]董景峰,周燕,许恒勤.面向内外部逆向物流的库存控制模型[J].计算机集成制造系统,2010(1)：64-69.
[45]张英.逆向物流中对回收品进行分类且随机的库存控制策略研究[J].物流工程与管理,2011(2)：52-55.
[46]张姣.供应链环境下含逆向物流的库存控制问题研究[J].商场现代化,2011(15)：45-46.
[47]陶琴.逆向物流链中库存控制模型的设计与仿真[D].江西：华东交通大学,2008.
[48]Stock J.R. Reverse Logistics[M]. Council of Logistics Management, Oak Brook, Illinois.1992.
[49]D.S. Rogers, Tibben-Lembke R.S. Going Backwards:reverse logistics trends and Practices[C]. Reverse Logistics Executive Council, Pittsburgh, PA,1999.
[50]de Brito M P, Dekker R. A Framework for Reverse Logistics. ERIM Report Series Research in Management,2003(045).
[51]郑晓娣,季建华.逆向物流的概念和分类研究[J].技术经济与管理研究,2004(1)：96-97.
[52]邹辉霞,荆海霞.基于供应链的逆向物流管理[J].中国流通经济,2003(7)：19-22.
[53]苏含秋,邓云霞.企业逆向物流模式的比较分析[J].物流科技,2006,29(129)：45.
[54]谢富慧.逆向物流中退货处理的速度分析[J].中国棉花加工,2005.4.
[55]胡长英.企业应重视循环经济视野下逆向物流的构建[J].中国工商报,2006.12.
[56]王红霞.逆向物流库存控制研究[D].大连：大连海事大学,2007.
[57]姚李刚,黄晓云,冯允成.基于多Agent概念的供应链仿真,武汉理工大学学报·信息与管理工程版[J].2003(1)：59-63.
[58]汪蓓蓓.面向库存管理的多Agent系统模拟模型研究[D].辽宁大连：大连海事大学,2006.
[59]朱福喜,朱三元,伍春香.大工智能基础[M].北京：清华大学出版社,2006.
[60]孟利清.基于Multi-Agent的林产品供应链管理研究——以云南省为例[D].江苏南京：南京林业大学,2009.
[61]姜丽红,刘豹等.股票智能预测支持系统的设计与实现.系统工程与市场经济[J].1996：473-480.
[62]张强.供应链环境下的多级库存管理研究[D].陕西西安：西北工业大学,2006.
[63]李英.多Agent系统及其在预测与智能交通系统中的应用[M].华东理工大学出版社,2004.
[64]周剑岚,冯珊.基于多Agent技术实现战略管理过程[J].华中理工大学学报,2000,28(7)：86-89.
[65]高曙,陈定方.基于多Agent的分布式虚拟设计/制造系统研究[J].计算机工程与应用,2002,38(22)：227-228,241.
[66]刘少锋.多Agent技术在供应链管理系统中的应用研究[D].陕西西安：西安理工大学,2005.
[67]范玉顺,曹军威.多代理系统理论、方法与应用[M].北京：清华大学出版社,2002,5.
[68]Finin T., Fritzson R., Mckay D., et al. KQML as an Agent Communication Language [C]. The 3rd International Conference on Information and Knowledge Management (CIKM94), ACM Press,1994,12.
[69]周剑岚,冯珊.基于多Agent技术实现战略管理过程[J].华中理工大学学报,2000, 28(7)：86-89.
[70]Zhao Tianzhi, Jin Yihui. Modeling Supply Chain Based on Multi-Agent System[J]. In: Proceedings of the 3th World Congress on Intelligent Control and Automation. China Hefei, 2000,268-271.
[71]Smith R. G. The contract net protocol:High-level communication and control in a distributed problem solver [J]. IEEE Transaction on Computers, C-29,1999(12):1104-1113.
[72]Smith R. G., Davis R. Framework for Cooperation in Distributed Problem Solving [J]. IEEE Transaction on System, Man and Cybernetics,1981,11(1):61-70.
[73]Lesser V. R., Erman L. D. Distributed Interpretation:a Model and Experiment [J]. IEEE Transaction on Computers,1981,29:1144-1163.
[74]Levesque H. J., Cohen P. R., Nunes J. On Acting Together [C]. In Proceedings of the National Conference on Artificial Intelligent (AAAI-1990), Menlo Park, California, AAAI Press,1990.
[75]Jennings N. R. Coordination Techniques for Distributed Artificial Intelligence [C]. In O'Hare GMP, Jennings N. R. eds, Foundation of Distributed Artificial Intelligence, John Willey & Sons,1996,187-210.
[76]刘贞,程勇军.Swarm for Java仿真及编程实现[M].北京：机械工业出版社,2009.
[77]王继荣.基于MAS再制造物流系统的库存控制研究[D].山东青岛：中国海洋大学,2005.
[78]杨浩.基于多Agent的敏捷化智能制造执行系统研究[D].江苏南京：南京航空航天大学,2004.
[79]王继荣.废旧家电回收再利用系统若干关键问题研究[D]. 山东青岛：中国海洋大学,2009.
[80]李睿.汽车工业集成化供应链的构建、管理与评价[D].湖北武汉：武汉理工大学,2005.
[81]宋手许.面向家电产品的逆向物流关键技术研究[D].安徽合肥：合肥工业大学,2007.
[82]魏灿生.逆向物流再制造系统生产与定价决策[D].大津：南开大学,2009.
[83]张思颖.基于智能Agent的仓储管理[D].重庆：重庆交通大学,2008.
[84]卢荣花.基于逆向物流的库存控制策略研究[D].江苏南京：南京航空航大大学,2007.
[85]何江海.逆向物流下库存控制策略研究[D].广东：广东外语外贸大学,2009.
[86]范文姬.不确定环境下的再制造物流系统库存控制与协调研究[D].北京：北京交通大学,2010.
[87]代应.废旧汽车资源化逆向物流运作管理研究[D].重庆：重庆交通大学,2008.
[88]洪丹.供应链管理下汽车制造企业生产性物料需求预测研究[D].湖北武汉：武汉理工大学,2007.
[89]李炜.供应链模式下我国汽车制造企业库存控制研究[D].湖北武汉：武汉理工大学,2006.
[90]彭维.含逆向物流的供应链库存控制研究[D].重庆：重庆交通大学,2008.
[91]胡小建,张敏,杨爱峰.闭环供应链中考虑退货价格影响的库存问题研究[J].合肥工业大学学报(自然科学版),2013(5)：616-620.
[92]马向国.含逆向物流的电子易逝品库存控制及仿真[J].中国流通经济,2013(1)：55-59.
[93]倪明,陶琴.基于MAS的逆向物流库存控制模型研究[J].微计算机信息,2009,25(11-2)：30-32.
[94]倪明,陶琴.基于Multi-Agent的供应链企业逆向物流库存模型研究[J].徐州工程学院学报(社会科学版),2009,24(1)：15-18.
[95]黄立川.基于Multi-Agent理论的制造业逆向物流库存模型[J].科技资讯,2008(34)：7-8.
[96]赵川,薛红.MAS在连锁零售企业多级库存控制中的应用研究[J].运筹与管理,2013(1)：252-255.
[97]许渲,朱金福.基于多目标规划的航空货运舱位存量控制模型[J].中国民航飞行学院学报,2013(5)：15-19.
[98]马林.汽车备件的多级库存管理研究[D].辽宁大连：大连海事大学,2009.
[99]张茂林.汽车分销渠道绩效评价研究[D].上海：同济大学,2007.
[100]耗雷.汽车零部件企业供应链环境下库存问题的研究[D].江苏南京：东南大学,2006.
[101]任文华.神龙汽车公司供应链库存管理优化[D].辽宁：辽宁工程技术大学,2003.
[102]朱小涛.我国汽车行业库存影响因素实证研究[D].广东：汕头大学,2004.
[103]杨浩.基于多Agent的敏捷化智能制造执行系统研究[D].江苏南京：南京航空航天大学,2004.
[104]郭俊荣.基于Multi-Agent的敏捷供应链管理的设计与实现[D].吉林：吉林大学,2008.
[105]A. Serdar Tasan, Mitsuo Gen. A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries[J]. Computers & Industrial Engineering, 2011,62(3):755-761.
[106]Ke Ke, Yue Jin, Haizheng Zhang. A Hybrid Push-Pull Model based MultiAgent Supply-Chain SystemWith Equilibrium Analysis[C].2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology,457-463.
[107]Quan Liu, Sherry X. Sun, Huaiqing Wang, Jing Zhao. A multi-agent based system for e-procurement exception management J]. Knowledge-Based Systems,2011 (24):49-57.
[108]Kwon OB, Lee JJ. A multi-agent intelligent system for efficient ERP maintenance [J]. Expert Systems witn Applications,2001,21 (4):191-202.
[109]Adamo Alfredo, Cafaro Luigi, Loia Vincenzo. A Multi-layered Agent Ontology System for Resource Inventory[J]. IEEE International Symposium on Industrial Electronics, Cambridge, ENGLAND,2008:2016-2021.
[110]Donald S, Allen. A multi-sector inventory model [J]. Journal of Economic Behavior & Organization,1997(32):55-87.
[111]Jovita Mercedes Hojas Baenas, Rosani de Castro, Rosane Aparecida Gomes Battistelle, Jose Alcides Gobbo Junior. A study of reverse logistics flow management in vehicle battery industries in the midwest of the state of Sao Paulo (Brazil) [J]. Journal of Cleaner Production,2011(19):168-172.
[112]Wen-Yau Liang, Chun-Che Huang. Agent-based demand forecast in multi-echelon supply chain[J]. Decision Support Systems,2006(42):390-407.
[113]YulanWang, PaulZipkin. Agents'incentives under buy-back contracts in a two-stage supply chain[J]. Int. J. Production Economics,2009 (120):525-539.
[114]Sherry X. Sun, Jing Zhao, Huaiqing Wang. An agent based approach for exception handling in e-procurement management [J]. Expert Systems with Applications:2012 (39): 1174-1182.
[115]V. Ravi, Ravi Shankar. Analysis of interactions among the barriers of reverse logistics [J]. Technological Forecasting & Social Change,2005(72):1011-1029.
[116]Karen Bush, Mark Macielag and Michele Weidner-Wells. Taking inventory:antibacterial agents currently at or beyond Phase 1[J]. Current opinion microbiology,2004(7):466-476.
[117]Chengzhi Jiang, Zhaohan Sheng. Case-based reinforcement learning for dynamic inventory control in a multi-agent supply-chain system[J]. Expert Systems with Applications,2009 (36):6520-6526.
[118]R. Glenn Richeya, Haozhe Chenb, Stefan E. Genchevb, Patricia J. Daugherty. Developing effective reverse logistics programs[J]. Industrial Marketing Management,2005 (34):830-840.
[119]Ezutah Udoncy Olugu, Kuan Yew Wong, Awaludin Mohamed Shaharoun. Development of key performance measures for the automobile green supply chain[J]. Resources, Conservation and Recycling,2011(55):567-579.
[120]Chad W. Autry. Formalization of reverse logistics programs:A strategy for managing liberalized returns[J]. Industrial Marketing Management,2005(34):749-757.
[121]Jun-Yeon Leea, Leroy B. Schwarz. Leadtime reduction in a (Q, r) inventory system:An agency perspective[J]. Int. J. Production Economics,2007(105):204-212.
[122]Chengzhi Jiang, Zhaohan Sheng. Learning framework for multi-agent simulation of supply chain systems[C]. International Conference on Computer Science and Information Technology 2008:425-431.
[123]D. Adebanjo, P. Xiao. Managing reverse logistics in the Chinese automobile industry[C]. IEEE International Conference on Management of Innovation and Technology,2006:834-838.
[124]Ahn HJ, Park SJ. Modeling of a Multi-agent System for Coordination of Supply Chains with Complexity and Uncertainty[C].6th Pacific Rim International Workshop on Multi-Agents, Seoul South Korea,2003:13-24.
[125]Chang Ouk Kim, Ick-Hyun Kwon, Choonjong Kwak. Multi-agent based distributed inventory control model[J]. Expert Systems with Applications,2010 (37):5186-5191.
[126]Pascal Forget, Sophie D Amours, Jean-Marc Frayret. Multi-behavior agent model for planning in supply chains:An application to the lumber industry[J]. Robotics and Computer-Integrated Manufacturing,2008 (24):664-679.
[127]A.Pan, S.Y.S. Leung, K.L. Moon, K.W. Yeung. Optimal reorder decision-making in the agent-based apparel supply chain[J]. Expert Systems with Applications 2009 (36): 8571-8581.
[128]Zhang Qi, Wang Hongcheng. Research on Construction Mode of Recycling Network of Reverse Logistics of Automobile Enterprises[C]. International Conference on Information Management, Innovation Management and Industrial Engineering,2008:36-40.
[129]Reynaldo Cruz-Rivera, Jurgen Ertel. Reverse logistics network design for the collection of End-of-Life Vehicles in Mexico[J]. European Journal of Operational Research 2009 (196):930-939.
[130]Wang Jirong, Li Jun, Zhang Yunhong, Hu Zongwu. Simulation Study on Influences of Information Sharing to Supply Chain Inventory System Based on Multi-agent System[C]. Proceedings of the IEEE International Conference on Automation and Logistics Qingdao, China September 2008:1001-1004.
[131]ZHU Xiaoyu, LI Xiaojiu. Study On A New System for Inventory Control[C]. International Conference on Intelligent Computation Technology and Automation,2008:718-720.
[132]Marijn Janssen. The architecture and business value of a semi-cooperative, agent-based supply chain management system[J]. Electronic Commerce Research and Applications, 2005(4):315-328.
[133]Wenfeng Li, Chunmeng Li. Transshipment Policy Research of Multi-Location Inventory System Based on Multi-Agent System[C]. Proceedings of the IEEE International Conference on Automation and Logistics, Qingdao China,2008:1344-1351.
[134]Hyunsoo Kima, Jaehwan Yang, Kang-Dae Lee. Vehicle routing in reverse logistics for recycling end-of-life consumer electronic goods in South Korea[J]. Transportation Research Part D,2009(14):291-299.
[135]Chan Felix T. S., Chan H. K., Jain Vipul.A framework of reverse logistics for the automobile industry. International journal of production research,2012,50(5):1318-1331.
[136]Inventory management in reverse logistics-analysis of Croatian automotive industry postsale practices. Tehnicki vjesnik-technical gazette,2013,20(3):541-547.
[137]Jonrinaldi; Zhang, D. Z. An integrated production and inventory model for a whole manufacturing supply chain involvingreverse logistics with finite horizon period. OMEGA-International journal of management science,2013,41(3):598-620
[138]Zerhouni Hichem, Gay on Jean-Philippe, Frein Yannick. Influence of dependency between demands and returns in a reverse logistics system. International Conference on Industrial Engineering and Systems Management (IESM), Montreal, CANADA,2009,143(1): 62-71
[139]Kannan Devika, Diabat Ali, Alrefaei Mahmoud. A carbon footprint based reverse logistics network design model. Resources conservation and recycling,2012(44):94-103
[140]Hazen Benjamin T., Hall Dianne J., Hanna Joe B. Reverse logistics disposition decision-making developing a decision framework via content analysis. International journal of physical distribution & logistics management,2012,42(3):244-274
[141]Alinovi Alberto, Bottani Eleonora, Montanari Roberto. Reverse Logistics:a stochastic EOQ-based inventory control model for mixed manufacturing/remanufacturing systems with return policies. International journal of production research,2012,50(5):1243-1264
[142]Lieckens K., Vandaele N. Multi-level reverse logistics network design under uncertainty. International journal of production research,2012,50(1):23-40
[143]Niknejad A., Petrovic D.. Optimisation of integrated reverse logistics networks with different product recovery routes[J]. European Journal of Operational Research, 2014(238):143-154.
[144]Jiang Zhigang, Zhu Shuo, Zhang Hua. Optimal Acquisition and Inventory Control for a Remanufacturing System. Discrete Dynamics in Nature and Society,2013 (2013):1-7.
[145]S.D.P. Flappera, J.P. Gayonb, S. Vercraene. Control of a production-inventory system with returns under imperfect advance return information[J]. European Journal of Operational Research,2012(218):392-400.
[146]Yaoqun Xu, Xinning Zhu. Research on Information Sharing Problem in Retailer-dominant Supply Chain Based on the MAS[C].25th Chinese Control and Decision Conference (CCDC),Guiyang,China,2013:1023-1028.
[147]Mahsa Parvini, Ali Atashi, S. Mohammad Moattar Husseini, Akbar Esfahanipour. A two-echelon inventory model with product returns considering demands dependent return rates. The International Journal of Advanced Manufacturing Technology,2014(72): 107-118.
[148]Tomasic D, Dukic G, Safran M. Inventory management in reverse logistics-analysis of Croatian automotive industry postsale practices. Tehnicki vjesnik-technical gazette, 2013(3):541-547.
[149]Onur Kaya, Fatih Bagci, Metin Turkay. Planning of capacity, production and inventory decisions in a generic reverse supply chain under uncertain demand and returns. International Journal of Production Research,2014(52):270-282.
[150]Xiaoming Li. Managing Dynamic Inventory Systems with Product Returns:A Markov Decision Process. Journal of Optimization Theory and Applications,2013(2):577-592.
[151]雷星晖,苏涛永.供应链参考模型中基于智能体的库存管理研究[J].同济大学学报(自然科学版),2006,34(2)：270-274.
[152]罗衡郴,张臻,周晓辉。基于Agent的库存管理系统[J].宁波职业技术学院学报,2007,11(5),21-23.
[153]余福茂,王富忠,沈祖志。基于CORBA技术的多Agent智能库存管理系统[J].物流技术,2006(3)：82-84.
[154]张铁柱,毛玮.基于Multi-Agent的供应链库存策略仿真研究[J].哈尔滨理工大学学报,2008,13(5)：87-90,94.
[155]马玉娟,吴旻.基于组库存策略和多Agent技术的库存管理模型.物流技术,2009,28(2)：77-79.
[156]卢荣花,宁宜熙,谢忠赞.逆向物流确定型库存控制策略研究.价值工程,2007(5)：101-105.
[157]徐长静,徐尔.逆向物流的多品种库存控制策略研究[J].物流技术,2006,29(136)：98-100.
[158]董景峰,周燕,许恒勤.面向内外部逆向物流的库存控制模型[J].计算机集成制造系统,2010,16(1)：64-69.
[159]松守许,朱华炳,周文广‘.允许退货和缺货条件下的逆向物流库存模型[J].物流技术,2007,26(10)：53-58.
[160]操露,韩瑞珠.基于多产品的动态回收系统库存优化研究[J].武汉理工大学学报(信息与管理工程版),2010,32(2)：341-344.
[161]马向国.基于电子产品易逝性的逆向物流库存控制仿真研究[J].中国市场,2013(18)：15-17,24.
[162]陈铓,龚存宇.考虑最低允许质量水平的逆向物流生产库存模型及其粒子群算法.湖南工程学院学报(自然科学版),2012(2)：20-24.
[163]张雅.逆向物流库存控制理论与应用.甘肃科学学报,2012(4)：107-109.
[2]李正锋.基于SWOT矩阵评析我国汽车企业逆向物流[J].华东经济治理,2007：61-63.
[3]阮略成,李杰.第三方汽车逆向物流模式浅析[J].汽车工业研究,2006：39-41.
[4]Laan E., Dekker R., Salomon M. Product Remanufacturing and Disposal:A Numerical Comparison of Alternative Strategies[J]. International Journal of Production Economics.1996,45.489-498.
[5]Schardy D A. A Deterministic Inventory Model for Repairable Items[J]. Naval Research Logistics Quarterly,1967,14:391-398.
[6]Mabini M C, Pintelon L M, Gelders L F. EOQ type formulations for controlling repairable inventories[J]. International Journal of Production Economics,1992,28:21-23.
[7]Richter K. The EOQ Repair and Waste Disposal Model with Variable Setup Numbers [J]. European Journal of Operational Research,1996,95:313-324.
[8]Richter K. The Extended EOQ Repair and Waste Disposal Model[J]. International Journal of Production Economics,1996,45:443-448.
[9]Teunter R.H.. Economic ordering quantities for recoverable item inventory systems [J]. Naval Research Logistics,2001,48:484-495.
[10]Minner S. Strategic safety stocks in reverse logistics supply chains[J]. International Journal of Production Economics,2001,71(3):417-428.
[11]Kleber R, Minner S, Kiesmuller G. A Continuous Time Inventory Model for a Product Recovery System with Multiple Options[J]. International Journal of Production Economics, 2002,79:121-141.
[12]Dobos I. Optimal Production-inventory Strategies for a HMMS-type Reverse Logistics System[J]. International Journal of Production Economics,2003,81-82:351-360.
[13]Kiesmuller G, Minner S. Simple expressions for finding recovery system inventory control parameter values[J]. Journal of the Operational Research Society.2003,54:83-88.
[14]Simpson V.P. Optimum solution structure for a repairable inventory problem[J]. Operations Research,1978,26 (2):270-281.
[15]Indefurth K. Simple optimal replenishment and disposal policies for product recovery system with lead times[J]. OR Spectrum,1997,19(2):111-222.
[16]Cohen MA, Nahmias S, Pierskalla W. A dynamic inventory system with recycling[J]. Naval Research Logistics Quarterly,1980,27(2):89-96.
[17]Kelle P, Silver E A. Purchasing policy of new containers considering the random returns of previously issued containers[J]. IIE Transactions,1989,21 (4):349-354.
[18]Buchanan D.J., Abad P. L. Optimal policy for a periodic review returnable inventory system[J]. IIE Transactions,1998,30:1049-1055.
[19]Toktay LB, Wein M, Zenios SA. Inventory management of remanufacturable products[J]. Management Science,2000,46(11):1412-1426.
[20]Kiesmuller G, Laan E.A., van der. An inventory model with dependent product demands and returns[J]. International Journal of Production Economics,2001,72:73-87.
[21]Teunter R.H., Vlachos D. On the necessity of a disposal option for returned items that can be remanufactured[J]. International Journal of Production Economics,2002,75:257-266.
[22]Mahadevan B, Pyke D.F., Fleischmann M. Periodic review, push inventory policies for remanufacturing[J]. European Journal of Operational Research,2003,151 (3):536-551.
[23]Mostard J, Koster R.D., Teunter R. The distribution-free newsboy problem with resalable returns[J]. International Journal of Production Economics,2003,97 (3):329-342.
[24]Vlachos D, Dekker R. Return handling options and order quantities for single period products[J]. European Journal of Operational Research,2003,151 (1):38-52.
[25]Adel A. Alamri. Theory and methodology on the global optimal solution to a GeneralReverse Logistics Inventory Model for deteriorating items andtime-varying rates[J]. Computers & Industrial Engineering,2011,60(2):236-247.
[26]Heyman D.P. Optimal disposal policies for a single-item inventory system with returns[J]. Naval Research Logistics Quarterly,1977,24:385-405.
[27]Muckstadt JA, Isaac MH. An analysis of single item inventory systems with returns[J]. Naval Research Logistics Quarterly,1981,28(2):37-54.
[28]Van D L E, Dekker R, Salomon M. An(s, Q)inventory model with remanufacturing and disposal [J]. International Journal of Production Economics,1996,46-47(3):339-350.
[29]Yuan X.M, Cheung K.L.. Modeling returns of merchandise in an inventory system[J]. OR Spectrum,1998,20 (3):147-154.
[30]Fleischmann M, Kuik R, Dekker R. Controlling Inventories with Stochastic Item Returns: a Basic Model[J]. European Journal of Operational Research,2002,138:63-75.
[31]Ahmed M.A. El Saadany. Mohamad Y. Jaber. A production/remanufacturing inventory model with price and quality dependant return rate[J]. Computers & Industrial Engineering, 2010:352-362.
[32]黄祖庆,达庆利.一个允许退货的库存控制策略模型[J].东南大学学报(自然科学版),2003,33(6)：792-795.
[33]陈秋双,刘东红.再制造系统的库存控制研究[J].南开大学学报(自然科学版),2003,36(3)：67-72.
[34]姚卫新.再制造条件下逆向物流回收模式的研究[J].管理科学,2004,17(1)：76-80
[35]黄祖庆,达庆利,王冬冬.逆向物流具有时滞的一个EOQ扩展订货模型[J].物流技术,2004,(5)：82-84.
[36]侯云章,戴更新,于庆东.二次订货策略在单周期产品逆向供应链中应用[J].系统工程理论与实践,2005,25(11)：35-40.
[37]杨杰,周磊山,孟翀,刘佳.包含逆向物流的供应链库存控制问题研究[J].北京交通大学学报,2006,(2)：15-18.
[38]李新军,达庆利.一种新型的再制造条件下EOQ模型[J].东南大学学报：自然科学版,2006,36(4)：667-671.
[39]黄祖庆,达庆利.基于逆向物流定期和定量处理的最优库存控制策略研究[J].东南大学学报(自然科学版),2005,35(2)：302-307.
[40]赵宜,蒲云,尹传忠.回收物流库存控制研究[J].中国管理科学,2005,13(5)：49-53.
[41]李常洪,石磊.一次逆向物流循环的库存控制模型探讨[J].物流技术,2009(10)：65-68.
[42]江玮璠,李文.基于蒙特卡罗的逆向物流库存控制研究[J].南吕工程学院学报,2010(3)：51-54.
[43]任鹏,邓书显.包含逆向物流的库存控制模型研究[J].西华大学学报(自然科学版),2010,29(4)：56-59.
[44]董景峰,周燕,许恒勤.面向内外部逆向物流的库存控制模型[J].计算机集成制造系统,2010(1)：64-69.
[45]张英.逆向物流中对回收品进行分类且随机的库存控制策略研究[J].物流工程与管理,2011(2)：52-55.
[46]张姣.供应链环境下含逆向物流的库存控制问题研究[J].商场现代化,2011(15)：45-46.
[47]陶琴.逆向物流链中库存控制模型的设计与仿真[D].江西：华东交通大学,2008.
[48]Stock J.R. Reverse Logistics[M]. Council of Logistics Management, Oak Brook, Illinois.1992.
[49]D.S. Rogers, Tibben-Lembke R.S. Going Backwards:reverse logistics trends and Practices[C]. Reverse Logistics Executive Council, Pittsburgh, PA,1999.
[50]de Brito M P, Dekker R. A Framework for Reverse Logistics. ERIM Report Series Research in Management,2003(045).
[51]郑晓娣,季建华.逆向物流的概念和分类研究[J].技术经济与管理研究,2004(1)：96-97.
[52]邹辉霞,荆海霞.基于供应链的逆向物流管理[J].中国流通经济,2003(7)：19-22.
[53]苏含秋,邓云霞.企业逆向物流模式的比较分析[J].物流科技,2006,29(129)：45.
[54]谢富慧.逆向物流中退货处理的速度分析[J].中国棉花加工,2005.4.
[55]胡长英.企业应重视循环经济视野下逆向物流的构建[J].中国工商报,2006.12.
[56]王红霞.逆向物流库存控制研究[D].大连：大连海事大学,2007.
[57]姚李刚,黄晓云,冯允成.基于多Agent概念的供应链仿真,武汉理工大学学报·信息与管理工程版[J].2003(1)：59-63.
[58]汪蓓蓓.面向库存管理的多Agent系统模拟模型研究[D].辽宁大连：大连海事大学,2006.
[59]朱福喜,朱三元,伍春香.大工智能基础[M].北京：清华大学出版社,2006.
[60]孟利清.基于Multi-Agent的林产品供应链管理研究——以云南省为例[D].江苏南京：南京林业大学,2009.
[61]姜丽红,刘豹等.股票智能预测支持系统的设计与实现.系统工程与市场经济[J].1996：473-480.
[62]张强.供应链环境下的多级库存管理研究[D].陕西西安：西北工业大学,2006.
[63]李英.多Agent系统及其在预测与智能交通系统中的应用[M].华东理工大学出版社,2004.
[64]周剑岚,冯珊.基于多Agent技术实现战略管理过程[J].华中理工大学学报,2000,28(7)：86-89.
[65]高曙,陈定方.基于多Agent的分布式虚拟设计/制造系统研究[J].计算机工程与应用,2002,38(22)：227-228,241.
[66]刘少锋.多Agent技术在供应链管理系统中的应用研究[D].陕西西安：西安理工大学,2005.
[67]范玉顺,曹军威.多代理系统理论、方法与应用[M].北京：清华大学出版社,2002,5.
[68]Finin T., Fritzson R., Mckay D., et al. KQML as an Agent Communication Language [C]. The 3rd International Conference on Information and Knowledge Management (CIKM94), ACM Press,1994,12.
[69]周剑岚,冯珊.基于多Agent技术实现战略管理过程[J].华中理工大学学报,2000, 28(7)：86-89.
[70]Zhao Tianzhi, Jin Yihui. Modeling Supply Chain Based on Multi-Agent System[J]. In: Proceedings of the 3th World Congress on Intelligent Control and Automation. China Hefei, 2000,268-271.
[71]Smith R. G. The contract net protocol:High-level communication and control in a distributed problem solver [J]. IEEE Transaction on Computers, C-29,1999(12):1104-1113.
[72]Smith R. G., Davis R. Framework for Cooperation in Distributed Problem Solving [J]. IEEE Transaction on System, Man and Cybernetics,1981,11(1):61-70.
[73]Lesser V. R., Erman L. D. Distributed Interpretation:a Model and Experiment [J]. IEEE Transaction on Computers,1981,29:1144-1163.
[74]Levesque H. J., Cohen P. R., Nunes J. On Acting Together [C]. In Proceedings of the National Conference on Artificial Intelligent (AAAI-1990), Menlo Park, California, AAAI Press,1990.
[75]Jennings N. R. Coordination Techniques for Distributed Artificial Intelligence [C]. In O'Hare GMP, Jennings N. R. eds, Foundation of Distributed Artificial Intelligence, John Willey & Sons,1996,187-210.
[76]刘贞,程勇军.Swarm for Java仿真及编程实现[M].北京：机械工业出版社,2009.
[77]王继荣.基于MAS再制造物流系统的库存控制研究[D].山东青岛：中国海洋大学,2005.
[78]杨浩.基于多Agent的敏捷化智能制造执行系统研究[D].江苏南京：南京航空航天大学,2004.
[79]王继荣.废旧家电回收再利用系统若干关键问题研究[D]. 山东青岛：中国海洋大学,2009.
[80]李睿.汽车工业集成化供应链的构建、管理与评价[D].湖北武汉：武汉理工大学,2005.
[81]宋手许.面向家电产品的逆向物流关键技术研究[D].安徽合肥：合肥工业大学,2007.
[82]魏灿生.逆向物流再制造系统生产与定价决策[D].大津：南开大学,2009.
[83]张思颖.基于智能Agent的仓储管理[D].重庆：重庆交通大学,2008.
[84]卢荣花.基于逆向物流的库存控制策略研究[D].江苏南京：南京航空航大大学,2007.
[85]何江海.逆向物流下库存控制策略研究[D].广东：广东外语外贸大学,2009.
[86]范文姬.不确定环境下的再制造物流系统库存控制与协调研究[D].北京：北京交通大学,2010.
[87]代应.废旧汽车资源化逆向物流运作管理研究[D].重庆：重庆交通大学,2008.
[88]洪丹.供应链管理下汽车制造企业生产性物料需求预测研究[D].湖北武汉：武汉理工大学,2007.
[89]李炜.供应链模式下我国汽车制造企业库存控制研究[D].湖北武汉：武汉理工大学,2006.
[90]彭维.含逆向物流的供应链库存控制研究[D].重庆：重庆交通大学,2008.
[91]胡小建,张敏,杨爱峰.闭环供应链中考虑退货价格影响的库存问题研究[J].合肥工业大学学报(自然科学版),2013(5)：616-620.
[92]马向国.含逆向物流的电子易逝品库存控制及仿真[J].中国流通经济,2013(1)：55-59.
[93]倪明,陶琴.基于MAS的逆向物流库存控制模型研究[J].微计算机信息,2009,25(11-2)：30-32.
[94]倪明,陶琴.基于Multi-Agent的供应链企业逆向物流库存模型研究[J].徐州工程学院学报(社会科学版),2009,24(1)：15-18.
[95]黄立川.基于Multi-Agent理论的制造业逆向物流库存模型[J].科技资讯,2008(34)：7-8.
[96]赵川,薛红.MAS在连锁零售企业多级库存控制中的应用研究[J].运筹与管理,2013(1)：252-255.
[97]许渲,朱金福.基于多目标规划的航空货运舱位存量控制模型[J].中国民航飞行学院学报,2013(5)：15-19.
[98]马林.汽车备件的多级库存管理研究[D].辽宁大连：大连海事大学,2009.
[99]张茂林.汽车分销渠道绩效评价研究[D].上海：同济大学,2007.
[100]耗雷.汽车零部件企业供应链环境下库存问题的研究[D].江苏南京：东南大学,2006.
[101]任文华.神龙汽车公司供应链库存管理优化[D].辽宁：辽宁工程技术大学,2003.
[102]朱小涛.我国汽车行业库存影响因素实证研究[D].广东：汕头大学,2004.
[103]杨浩.基于多Agent的敏捷化智能制造执行系统研究[D].江苏南京：南京航空航天大学,2004.
[104]郭俊荣.基于Multi-Agent的敏捷供应链管理的设计与实现[D].吉林：吉林大学,2008.
[105]A. Serdar Tasan, Mitsuo Gen. A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries[J]. Computers & Industrial Engineering, 2011,62(3):755-761.
[106]Ke Ke, Yue Jin, Haizheng Zhang. A Hybrid Push-Pull Model based MultiAgent Supply-Chain SystemWith Equilibrium Analysis[C].2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology,457-463.
[107]Quan Liu, Sherry X. Sun, Huaiqing Wang, Jing Zhao. A multi-agent based system for e-procurement exception management J]. Knowledge-Based Systems,2011 (24):49-57.
[108]Kwon OB, Lee JJ. A multi-agent intelligent system for efficient ERP maintenance [J]. Expert Systems witn Applications,2001,21 (4):191-202.
[109]Adamo Alfredo, Cafaro Luigi, Loia Vincenzo. A Multi-layered Agent Ontology System for Resource Inventory[J]. IEEE International Symposium on Industrial Electronics, Cambridge, ENGLAND,2008:2016-2021.
[110]Donald S, Allen. A multi-sector inventory model [J]. Journal of Economic Behavior & Organization,1997(32):55-87.
[111]Jovita Mercedes Hojas Baenas, Rosani de Castro, Rosane Aparecida Gomes Battistelle, Jose Alcides Gobbo Junior. A study of reverse logistics flow management in vehicle battery industries in the midwest of the state of Sao Paulo (Brazil) [J]. Journal of Cleaner Production,2011(19):168-172.
[112]Wen-Yau Liang, Chun-Che Huang. Agent-based demand forecast in multi-echelon supply chain[J]. Decision Support Systems,2006(42):390-407.
[113]YulanWang, PaulZipkin. Agents'incentives under buy-back contracts in a two-stage supply chain[J]. Int. J. Production Economics,2009 (120):525-539.
[114]Sherry X. Sun, Jing Zhao, Huaiqing Wang. An agent based approach for exception handling in e-procurement management [J]. Expert Systems with Applications:2012 (39): 1174-1182.
[115]V. Ravi, Ravi Shankar. Analysis of interactions among the barriers of reverse logistics [J]. Technological Forecasting & Social Change,2005(72):1011-1029.
[116]Karen Bush, Mark Macielag and Michele Weidner-Wells. Taking inventory:antibacterial agents currently at or beyond Phase 1[J]. Current opinion microbiology,2004(7):466-476.
[117]Chengzhi Jiang, Zhaohan Sheng. Case-based reinforcement learning for dynamic inventory control in a multi-agent supply-chain system[J]. Expert Systems with Applications,2009 (36):6520-6526.
[118]R. Glenn Richeya, Haozhe Chenb, Stefan E. Genchevb, Patricia J. Daugherty. Developing effective reverse logistics programs[J]. Industrial Marketing Management,2005 (34):830-840.
[119]Ezutah Udoncy Olugu, Kuan Yew Wong, Awaludin Mohamed Shaharoun. Development of key performance measures for the automobile green supply chain[J]. Resources, Conservation and Recycling,2011(55):567-579.
[120]Chad W. Autry. Formalization of reverse logistics programs:A strategy for managing liberalized returns[J]. Industrial Marketing Management,2005(34):749-757.
[121]Jun-Yeon Leea, Leroy B. Schwarz. Leadtime reduction in a (Q, r) inventory system:An agency perspective[J]. Int. J. Production Economics,2007(105):204-212.
[122]Chengzhi Jiang, Zhaohan Sheng. Learning framework for multi-agent simulation of supply chain systems[C]. International Conference on Computer Science and Information Technology 2008:425-431.
[123]D. Adebanjo, P. Xiao. Managing reverse logistics in the Chinese automobile industry[C]. IEEE International Conference on Management of Innovation and Technology,2006:834-838.
[124]Ahn HJ, Park SJ. Modeling of a Multi-agent System for Coordination of Supply Chains with Complexity and Uncertainty[C].6th Pacific Rim International Workshop on Multi-Agents, Seoul South Korea,2003:13-24.
[125]Chang Ouk Kim, Ick-Hyun Kwon, Choonjong Kwak. Multi-agent based distributed inventory control model[J]. Expert Systems with Applications,2010 (37):5186-5191.
[126]Pascal Forget, Sophie D Amours, Jean-Marc Frayret. Multi-behavior agent model for planning in supply chains:An application to the lumber industry[J]. Robotics and Computer-Integrated Manufacturing,2008 (24):664-679.
[127]A.Pan, S.Y.S. Leung, K.L. Moon, K.W. Yeung. Optimal reorder decision-making in the agent-based apparel supply chain[J]. Expert Systems with Applications 2009 (36): 8571-8581.
[128]Zhang Qi, Wang Hongcheng. Research on Construction Mode of Recycling Network of Reverse Logistics of Automobile Enterprises[C]. International Conference on Information Management, Innovation Management and Industrial Engineering,2008:36-40.
[129]Reynaldo Cruz-Rivera, Jurgen Ertel. Reverse logistics network design for the collection of End-of-Life Vehicles in Mexico[J]. European Journal of Operational Research 2009 (196):930-939.
[130]Wang Jirong, Li Jun, Zhang Yunhong, Hu Zongwu. Simulation Study on Influences of Information Sharing to Supply Chain Inventory System Based on Multi-agent System[C]. Proceedings of the IEEE International Conference on Automation and Logistics Qingdao, China September 2008:1001-1004.
[131]ZHU Xiaoyu, LI Xiaojiu. Study On A New System for Inventory Control[C]. International Conference on Intelligent Computation Technology and Automation,2008:718-720.
[132]Marijn Janssen. The architecture and business value of a semi-cooperative, agent-based supply chain management system[J]. Electronic Commerce Research and Applications, 2005(4):315-328.
[133]Wenfeng Li, Chunmeng Li. Transshipment Policy Research of Multi-Location Inventory System Based on Multi-Agent System[C]. Proceedings of the IEEE International Conference on Automation and Logistics, Qingdao China,2008:1344-1351.
[134]Hyunsoo Kima, Jaehwan Yang, Kang-Dae Lee. Vehicle routing in reverse logistics for recycling end-of-life consumer electronic goods in South Korea[J]. Transportation Research Part D,2009(14):291-299.
[135]Chan Felix T. S., Chan H. K., Jain Vipul.A framework of reverse logistics for the automobile industry. International journal of production research,2012,50(5):1318-1331.
[136]Inventory management in reverse logistics-analysis of Croatian automotive industry postsale practices. Tehnicki vjesnik-technical gazette,2013,20(3):541-547.
[137]Jonrinaldi; Zhang, D. Z. An integrated production and inventory model for a whole manufacturing supply chain involvingreverse logistics with finite horizon period. OMEGA-International journal of management science,2013,41(3):598-620
[138]Zerhouni Hichem, Gay on Jean-Philippe, Frein Yannick. Influence of dependency between demands and returns in a reverse logistics system. International Conference on Industrial Engineering and Systems Management (IESM), Montreal, CANADA,2009,143(1): 62-71
[139]Kannan Devika, Diabat Ali, Alrefaei Mahmoud. A carbon footprint based reverse logistics network design model. Resources conservation and recycling,2012(44):94-103
[140]Hazen Benjamin T., Hall Dianne J., Hanna Joe B. Reverse logistics disposition decision-making developing a decision framework via content analysis. International journal of physical distribution & logistics management,2012,42(3):244-274
[141]Alinovi Alberto, Bottani Eleonora, Montanari Roberto. Reverse Logistics:a stochastic EOQ-based inventory control model for mixed manufacturing/remanufacturing systems with return policies. International journal of production research,2012,50(5):1243-1264
[142]Lieckens K., Vandaele N. Multi-level reverse logistics network design under uncertainty. International journal of production research,2012,50(1):23-40
[143]Niknejad A., Petrovic D.. Optimisation of integrated reverse logistics networks with different product recovery routes[J]. European Journal of Operational Research, 2014(238):143-154.
[144]Jiang Zhigang, Zhu Shuo, Zhang Hua. Optimal Acquisition and Inventory Control for a Remanufacturing System. Discrete Dynamics in Nature and Society,2013 (2013):1-7.
[145]S.D.P. Flappera, J.P. Gayonb, S. Vercraene. Control of a production-inventory system with returns under imperfect advance return information[J]. European Journal of Operational Research,2012(218):392-400.
[146]Yaoqun Xu, Xinning Zhu. Research on Information Sharing Problem in Retailer-dominant Supply Chain Based on the MAS[C].25th Chinese Control and Decision Conference (CCDC),Guiyang,China,2013:1023-1028.
[147]Mahsa Parvini, Ali Atashi, S. Mohammad Moattar Husseini, Akbar Esfahanipour. A two-echelon inventory model with product returns considering demands dependent return rates. The International Journal of Advanced Manufacturing Technology,2014(72): 107-118.
[148]Tomasic D, Dukic G, Safran M. Inventory management in reverse logistics-analysis of Croatian automotive industry postsale practices. Tehnicki vjesnik-technical gazette, 2013(3):541-547.
[149]Onur Kaya, Fatih Bagci, Metin Turkay. Planning of capacity, production and inventory decisions in a generic reverse supply chain under uncertain demand and returns. International Journal of Production Research,2014(52):270-282.
[150]Xiaoming Li. Managing Dynamic Inventory Systems with Product Returns:A Markov Decision Process. Journal of Optimization Theory and Applications,2013(2):577-592.
[151]雷星晖,苏涛永.供应链参考模型中基于智能体的库存管理研究[J].同济大学学报(自然科学版),2006,34(2)：270-274.
[152]罗衡郴,张臻,周晓辉。基于Agent的库存管理系统[J].宁波职业技术学院学报,2007,11(5),21-23.
[153]余福茂,王富忠,沈祖志。基于CORBA技术的多Agent智能库存管理系统[J].物流技术,2006(3)：82-84.
[154]张铁柱,毛玮.基于Multi-Agent的供应链库存策略仿真研究[J].哈尔滨理工大学学报,2008,13(5)：87-90,94.
[155]马玉娟,吴旻.基于组库存策略和多Agent技术的库存管理模型.物流技术,2009,28(2)：77-79.
[156]卢荣花,宁宜熙,谢忠赞.逆向物流确定型库存控制策略研究.价值工程,2007(5)：101-105.
[157]徐长静,徐尔.逆向物流的多品种库存控制策略研究[J].物流技术,2006,29(136)：98-100.
[158]董景峰,周燕,许恒勤.面向内外部逆向物流的库存控制模型[J].计算机集成制造系统,2010,16(1)：64-69.
[159]松守许,朱华炳,周文广‘.允许退货和缺货条件下的逆向物流库存模型[J].物流技术,2007,26(10)：53-58.
[160]操露,韩瑞珠.基于多产品的动态回收系统库存优化研究[J].武汉理工大学学报(信息与管理工程版),2010,32(2)：341-344.
[161]马向国.基于电子产品易逝性的逆向物流库存控制仿真研究[J].中国市场,2013(18)：15-17,24.
[162]陈铓,龚存宇.考虑最低允许质量水平的逆向物流生产库存模型及其粒子群算法.湖南工程学院学报(自然科学版),2012(2)：20-24.
[163]张雅.逆向物流库存控制理论与应用.甘肃科学学报,2012(4)：107-109.