林纸供应链原料供应优化与仿真研究
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摘要
造纸术是中国古代的“四大发明”之一,在人类历史留下了灿烂的一页。二十一世纪信息时代、电子时代的来临也没能动摇纸产品在社会各方面发展中的重要地位。中国的森林资源比较有限,由于长期的砍伐和利用,全国不少地区的可利用资源已经濒临枯竭。传统林、浆、纸三个环节分离的模式已经造成了原材料供应需求很大,这必然造成木材资源供应的缺口。纸张生产和林木资源一体化的模式可以抵御由于原材料价格的波动带来的企业生存危机,保证林木资源长期稳定供应;同时,一体化集团内部进行利益的再分配,实现整体利益的最大化,能够抵御外部经济的波动给集团企业带来的冲击。
     林纸一体化供应链原料供应管理是林纸供应链管理最核心的部分,原料供应管理的目标是能保证造纸使用的植物纤维稳定可持续地供应,避免原料价格出现剧烈的波动和原料供应的短缺。
     目前林纸集团木片库存积压严重,造成原料时间性损耗严重和原料质量下降;纸产品的库存不能在短期内消化,造成资金的大量占用;产能在纸产品的品种上分配不合理,不能最大限度的满足客户对纸产品的需求;不能实现均衡生产,导致生产运作成本较高。针对这些情况,本文提出了林纸供应链原料供应短期优化的综合性解决方案。林纸供应链原料供应短期优化首先是对纸产品的销售进行预测,然后基于销售预测的结果进行排产优化,使产能合理分配,最后基于排产优化的结果,制定木材纤维原料的供应策略和供应计划。通过林纸供应链原料供应的短期优化,实现造纸原料的需求与供给平衡,既保证企业生产的平顺性,又实现节约型生产,降低林纸集团的生产运作成本,提高纸产品的收益率。文中以HF公司为例,进行了林纸供应链原料供应短期优化的应用研究,取得了较好的效果。
     为了规避了中长期木材原料的供应短缺、产能过剩等风险,保证林纸集团造纸用木材的供应安全,实现造纸木材原料的可持续供应;实现林木的经济价值、生态效益、社会效益相统一,促进林业经济和区域生态的可持续发展,在此前提下实现林木经济价值的最大化,即采取合理的采伐方案和林地种植面积实现林地木材产出的最大化。为了实现以上目标,本文建立了林纸供应链原料供应的中长期仿真控制系统。首先,完成仿真计算前的准备工作,包括建立仿真运算约束环境(纸张销量预测模型、木材采购预测模型和林木生长模型),设置仿真控制目标(战略规划期,可控林地形成稳定木材供应的目标过度期和木材过度期之后木材的对外依存率),输入仿真控制变量(林地的种植面积,林木的砍伐方案和林木战略储备水平);然后,进行林纸供应链原料供应中长期仿真计算,并输出仿真结果(战略规划期内每年林地砍伐的木材量,战略规划期内每年采购的木材量,战略规划期内每年缺口的木材量,仿真结束时活立木的蓄积量,单位林地平均参考经济价值,战略规划期内可控林地形成稳定木材供应的过渡期,战略规划期内每年木材的对外依存率);分析仿真结果,对于部分年度出现木材自给供应不足和市场供应短缺的情况,仿真控制系统提供建议解决方案,即通过增加虚拟林地的供应,解决了木材原料供应短缺的问题;比较仿真输出结果,调整仿真控制变量,再次进行仿真运算;最后,遴选优秀仿真方案作为决策备选方案。
     林纸供应链原料供应的短期优化和中长期仿真与ERP系统的集成解决了优化和仿真可重用性和柔性差的难题。对于ERP系统来说,优化和仿真的功能是其决策支持的重要组成部分,随着企业对战略决策和优化的越来越重视,以及仿真和优化的理论和方法越来越成熟,ERP中决策支持模块将成为判断ERP竞争能力的重要指标。
Papermaking was one of the "four great inventions" of ancient China, and left a brilliantpage in the history of mankind. Information age of the21st century, the advent of the electronicage could not shake the important position of paper products in the development of all sectorsof society. China's forest resources are relatively limited, due to the long-term deforestation andthe available resources in many areas of the country are on the verge of depletion. Thetraditional mode of seperation of forest, pulp and paper has caused a great demand for thesupply of raw materials, which will inevitably lead to the supply gap of timber resource. Themodel of Forestry-Paper integration that can withstand the enterprises to survive the crisis dueto fluctuations in the prices of raw materials, to ensure a steady supply of long-term forestresources; At the same time, the internal redistribution of interests in integration Group in orderto maximize the overall interests of grouping can resist the impact of external economicfluctuations to the Group's business.
     Supply management of raw materials in Forestry-Paper integration supply chain is themost central part of Forestry-Paper integration supply chain. The objective of supplymanagements of raw materials is to ensure the sustainable supply of timber used inpapermaking plant to avoid dramatic fluctuations of raw material prices and supplyshortages ofraw materials.
     Currently, the serious backlog of wood chips in Forest&Paper Group has caused serioustimber loss and the descending in the quality of timber; Inventory of paper products can not besold in the short term, to cause capital occupied; Unreasonable distribution of productioncapacity on a variety of paper products, could not maximize to meet customer demand for paperproducts; Balanced production can not be achieved, to result in higher cost of production andoperation. For these situations, a comprehensive solution to optimization of short-term supplyof raw materials was proposed. Firstly, the optimization of Short-term supply of raw materialswas to predict the sales of paper products, then according to the results of the sales forecasting,production capacity was rationally allocated, and finally the strategy and planning of supply ofraw materials was scheduled. Short-term optimization of supply of raw material was helpful torealize the balance of demand and supply of materials. Not only smooth production but alsoeconomical production were achieved, the costs of production and operating was reduced, andthe yield of the paper products was improved.
     In order to avoid long-term supply shortages of raw material, overcapacity, and to ensurethe sustainable supply of timber in Forest&Paper Group, and on the premise of realizing theunification of the economic value, the forest ecological benefits and social benefits, promotingsustainable development of forestry economic and regional ecological, achieving themaximization of the economic value of the forest was required. In order to achieve the aboveobjectives, the long-term simulation control system of material supply based on Forestry-Papersupply chain was established. Firstly, preparation was ready for simulation, includingestablishment of the simulation constraint environment—paper sales forecasting model, timberprocurement forecasting model and tree growth model, the goal of simulation control was set—strategic planning, supply transition period of controllable woodland which formed a stable wood supply and the rate of timber external dependency, and the simulation variables was input—woodland quantity, tree felling programs and forest strategic reserve level; then calculation oflong-term simulation based on Forestry-Paper supply chain was executed and simulation resultswas put out—the amount of harvesting wood per year during strategic planning period, theamount of wood purchased each year during the strategic planning, the amount of shortage ofwood during strategic planning period, the volume of live trees at the end of the simulation, theaverage referenced economic value per woodland, supply transition period of controllablewoodland which formed a stable wood supply during strategic planning period, and the rate oftimber external dependency during strategic planning period; Suggest solutions to solve theproblem of shortage of wood supply by increasing the supply of virtual woodland; Compare theoutput of simulations, adjust the simulation control variables, and ran simulation again; Finally,select excellent simulation programs as decision-making options.
     The problems of poor reusability and flexibility of optimization and simulation weresolved by the integration of short-term optimization and long-term simulation of supply of rawmaterials based on Forestry-Paper supply chain with ERP system.
     Optimization and simulation were important parts of their decision-making support in ERPsystems. With the increasing emphasis on strategic decision-making and optimization, and moreand more mature of the theories and methods of simulation and optimization, supportingdecision-making in ERP system would be an important indicator to determine thecompetitiveness of ERP.
引文
[1] Adelantado M.Airport Simulation Using the High Level Architecture[C]//Proceedings of2001EuropeanSimulation Interoperability Workshop.Harrow:SISO,2001:721-726.
    [2] Alast V.Formalization and verification of Event-driven Process Chains[J].Information and SoftwareTechnology,1999,41(10):639-650.
    [3] Anglani A,Grieco A,Pacella M,Tolio T.Object-oriented Modeling and Simulation of FlexibleManufacturing Systems: a Rule-based Procedure[J]. Simulation Modelling Practice and Theory(S1569-190X),2002,10(10):209-234.
    [4] Athanasios A R,Athanasios J,Ilias P.Logistics issues of biomass:The storage problem and themulti-biomass supply chain[J].Renewable and Sustainable Energy Reviews,2009,13(4):887-894.
    [5] Bandinelli R,Rapaccini M,Tucci M,etal.Using Simulation for Supply Chain Analysis:Reviewing andProposing Distributed Simulation Frameworks[J].Production Planning&Control (S0953-7287),2006,17(2):167-175.
    [6] Bandinelli R,Rapaccini M,Tucci M,etal.Using Simulation for Supply Chain Analysis:Reviewing andProposing Distributed Simulation Frameworks[J].ProductionPlanning&Control,2006,17(2):167-175.
    [7] Banks J.The Future of Simulation[C].Proceedings of the European Simulation Multi-Conference,Ghent,Belgium.2000.
    [8] Beamon B M.Measuring supply chain performance[J].International Joural of Operations&ProductionManagement,1999,19(34):275-292.
    [9] Berg S.Harvesting technology and marke forces affecting the production of forest fuels from Swedishforestry[J].2003,24(4-5):381-388.
    [10] Bergstrom M,Stehn L.Matching industrialized timber frame housing needs and enterprise resource planning:A change process[J].International Journal of Production Economics,2005,97(2):172-184.
    [11] Bernhard J A,Marios C A.Sysetm Dynamics Modelling in Supply Chain Management:ResearchReview[C].Proceedings of the2000Winter simulation Conference,2000:342-351.
    [12] Brun A,Cavalieri S,Macchi M,et al.Distributed Simulation for Supply Chain Coordination[C]//Proceedingsof the12th International Working Seminar on Production Economics (S1424-8573).Innsbruck:Springer,2002:1132-1136.
    [13] Carlsson D, Ronnquist M. Supply chain management in forestry—Case studies at Sodra CellAB[J].Eupropean Journal of Operational Research,2005,163(11):589-616.
    [14] Chase RB, JacobsFR, Aquilano NJ. Operations Management for CompetitiveAdvantage(11thEdition)[M].McGraw-Hill/Irwin,2006.
    [15] Chauhan S S,Frayret J M,LeBel L.Multi-commodity supply network planning in the forest supplychain[J].European Journal of Operational Research,2009,196(2):688-696.
    [16] Chen D,Turner S J,W T Cai.A Framework for Robust HLA-based Distributed Simulations[C]//Proceedingsof the20th workshop on Principles of Advanced and Distributed Simulation (S1087-4097).Singapore:IEEE,2006:183-192.
    [17] Chopra S,Meindl P.Supply Chain Management:Stragegy,Planning,and Operation(4thEdition)[M].PrenticeHall,2010.
    [18] Dahmann J S,Kuhl F,Weatherly R.Standards for Simulation:As Simple As Possible But Not Simpler-TheHigh Level Architecture for Simulation[J].Simulation (S0037-5497),1998,71(6):378-387.
    [19] Dauvergne P,Lister J.Timber[M].Polity Press,2011.
    [20] Dean C C,Jack C H,Terry P H.A multi-formalism architecture for agent-based,order-centric supply chainsimulation[J].Simulation Modeling Practice&Theory (S1569-190X),2007,15(2):153-174.
    [21] Dean C C,Terry P H,Jack C H.SISCO:An object-oriented supply chain simulation system[J].DecisionSupport Systems (S0167-9236),2006,42(1):422-434.
    [22] Department of Defense.High Level Architecture Run-Time Infrastructure Programmer’s Guide1.3Version4[Z].Washington DC:DoD,1998:1-120.
    [23] Fabio B,Giovanni C,Dominic G.Developing multi-agent systems with JADE[M].USA:John Wiley&SonsLtd,2007.
    [24] Fernando D M,Gonzalo G,Antonio E,etal.An agent-based approach for supply chain retrofitting underuncertainty[J].Computers&Chemical Engineering (S0098-1354),2007,31(5/6):722-735.
    [25] Forget P.Amours S D,Frayret J M.Multi-behavior agent model for planning in supply chains:An applicationto the lumber industry[J].Robotics and Computer-Integrated Manufacturing,2008,24(5):664-679.
    [26] Fu M C.Optimization Using Simulation:a Review[J].Operations Research (S0030-364X),1994,42(2):199-248.
    [27] Fu-Ren Lin.Reengineering the Order Fulfillment Process in Supply Chain Networks.[J].The Internationalof Flexible Manufacturing.
    [28] Gan B P, Cai W, Turner S. Distributed Supply-chain Simulation Using High LevelArchitecture[J].Transactions of the Society for Computer Simulation (S0740-6797),2001,18(2):98–109.
    [29] Gan B P,Liu L,Jain S,et al.Distributed Supply Chain Simulation across Enterprise Boundaries[C]//Proceedings of the2000Winter Simulation Conference (S0891-7736).Orlando:ACM,2000:1245-1251.
    [30] Gronalt M,Rauch P.Designing a regional forest fuel aupply network[J].Biomass and Bioenergy,2007,31(6):393-402.
    [31] Gunnarsson H,Ronnquist M,Lundgre J T.Supply chain modeling of forest fuel[J].European Journal ofOperational Research,2004,158(1):103-123.
    [32] Gunnarsson H,Ronnquist M.Solving a multi-period supply chain problem for a pulp company usingheuristics—An application to Sodra Cell AB[J].International Journal of Production Economics,2008,116(1):75-94.
    [33] IBM Co. Glossary-Supply Chain Management. http://www-106.ibm.com/developerworks parrernsglossary/supply-chain-management.html.
    [34] IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA)-Framework and Rules2000[S].
    [35] Ikkai Y,Goossenaerts J,Komoda N.A simulation Method for Evaluation Product Family SupplyChain[A].19997th IEEE International Conference on[C].1999,1437-1441.
    [36] Jones P C, Ohlmann J W. Long-range timber supply planning for a vertically integrated papermill[J].European Journal of Operational Reaearch,2008,191(2):558-571.
    [37] Kelleret P, Tchernev N, Force C. Object-oriented Methodology for FMS Modeling andsimulation[J].International Journal of Computer Integrated Manufacturing (S1362-3052),1997,10(6):405-434.
    [38] Kelton W,Sadowski R,Sadowski D.Simulation with Arena[M].McGrawHill,1996.
    [39] Kratkiewicz G,Fedyk A,Cerys D.Integrating a Distributed Agent-based Simulation Into an HLAFederation[J/OL].(2004-05-08)[2006-03-03].http://ms.ieorg/SIW_LOG/siw_log_bibliography.shtml,SIW Logistics and Enterp riseModels Forum.
    [40] Kreutzer Wolfgang, Osterbye Kasper. Beta SIM-A Framework for Discrete Event Modeling andSimulation[J].Simulation Practice and Theory (S0928-4869),1998,6(6):573-599.
    [41] Krzysztof C,Maciej G,Pawel K,etal.Efficiency of JADE agent platform[J].Scientific Programming,2005,13:159-172.
    [42] Lee J S, Zeigler B P. Space-Based Communication Data Management in Scalable DistributedSimulation[J].Journal of Parallel and Distributed Computing (S0743-7315),2002,62(3):336-365.
    [43] Mertins K,Rabe M,Jakel F W.Distributed Modeling and Simulation of Supply Chains[J].InternationalJournal of Computer Integrated Manufacturing (S0951-192X),2005,18(5):342-344.
    [44] Minegishi, shotaro, Daniel T. System Dynamics and simulation of a particular Food SupplyChain[J].Simulation Practice and Theory,2000(8):321-339.
    [45] Moller B,Nielsen P S.Analyzing transport costs of Danish forest wood chip resources by means ofcontinuous cost surfaces[J].Biomass and Bioenergy,2007,31(5):291-298.
    [46] Nelson M,Roger B,Chris L.The Swarm Simulation System:A Toolkit for Building Multi-agentSimulations[EB/OL].(1996-6-21)[2002-3].http://www.swarm.org.
    [47] Ouhimmou M,Amours S D,Beauregard R,etal.Furniture supply chain tactical planning optimization Usinga time decomposition approach[J].European Journal of Operational Reaearch,2008,189(3):952-970.
    [48] Parunak Van,Vander B R.Modeling the extended supply newwork[R].Internal Report,1998.
    [49] PersonaA,etal.Optimal safety stock levels of subassemblies and manufacturing components[J].InternationalJournal of Production Economics,2007,110:147-159.
    [50] Sawhney A,Abudayyeh O.Modeling and Analysis of a Mail Processing Plant Using Petri Nets[J].Advancesin Engineering Software (S0965-9978),1999,30(8):543-549.
    [51] Schulze T,Steffen S,Ulrich K.Migration of HLA into Civil Domains:Solutions and Prototypes forTransportation Applications[J].Simulation (S0037-5497),1999,73(5):296-303.
    [52] Shen W, Barthes J P, Norrie D H. Multi-Agent Systems for Concurrent Intelligent Design andManufacturing[M].Taylor&Francis,2000.
    [53] Sikora R,Shaw M J.A Multi-Agent Framework for the Coordination and Integration of InformationSystems[J].Management Science1998,44(11):65-78.
    [54] Supply-Chain Council. SCOR-Supply Chain Operations Reference[EB/OL].2008. http://www.supply-chain.org.
    [55] Swaminathan J M, Haas W A, Smith S F. Modeling Supply Chain Dynamics: A MultiagentApproach[J].Decision Sciences,1998,29(3):607-632.
    [56] Troncoso J J,Garrido R A.Forestry production and logistics planning:an analysis using mixed-integraterprogramming[J].International Journal of Production Economics,2005,7(4):625-633.
    [57] Troy J Strader,Fu-Ren Lin,Michael J Shaw.Simulation of Order Fulfillment in Divergent Assembly SupplyChains.[J].Journal of Artificial Societies and Social Simulation (S1460-7425),1998,11(2):197-230.
    [58] Wang M H,Wang H Q,Vogel D,Kumar K,etal.Agent-based negotiation and decision making for dynamicsupply chain formation[J].Engineering Applications of Artificial Intelligence,2009,22(7):1046-1055.
    [59] Wang X,Turner S J,Low M Y H,et al.Optimistic Synchronization in HLA-based DistributedSimulation[J].Simulation (S0037-5497),2005,81(4):279-291.
    [60] White K Preston,Jr Barney Brian,Scott Keller A N.Object-oriented Paradigm for Simulation PostalDistribution Centers[C]//Proceedings of the2001Winter Simulation Conference.1999.
    [61] Wing Y H,Nouri J S,Nilay S.Object-oriented dynamic supply-chain modelling incorporated with productionscheduling[J].European Journal of Operational Research (S0377-2217),2006,169(3):1064-1076.
    [62] Yu L C,Steinman J S,Blank G E.Adapting Your Simulation for HLA[J].Simulation (S0037-5497),1998,71(6):410-420.
    [63] Zeilger B P,Kim D,Buckley S J.Distributed Supply Chain Simulation in a DEVS/CORBA ExecutionEnvironment[C].Proceedings of the1999Winter Simulation Conference (S0891-7736).
    [64]陈彩虹,郑贵军,邓德胜.营销预警系统在林产品物流中的应用[J].经济问题,2007(5):31-33.
    [65]邓拥军,房桂干,韩善明,等.木片储存对P-RCAPMP制浆性能的影响[J].中国造纸,2009,28(11):33-36.
    [66]邸彦强,柴旭东,李伯虎,等.HLA/RTI网格化与以模型为中心的分布仿真互联模式研究[J].计算机集成制造系统,2006,12(4):504-510.
    [67]范文慧,肖田元,郭斌,等.基于HLA和DEVS的综合保障分布式仿真的研究[J].系统仿真学报,2006,18(2):300-303.
    [68]高翔,林杰,张炜.基于Agent的供应链仿真模型设计与实现[J].计算机工程与应用,2005,(32):183-186.
    [69]郭斌,范文慧,熊光楞.基于HLA/DEVS的协同仿真高层建模研究[J].系统仿真学报,2006,18(8):2174-2178.
    [70]韩洋,柴跃廷.柔性供应链仿真系统的参考架构[J].系统仿真学报,2011,23(04):681-686.
    [71]韩洋,柴跃廷.柔性供应链仿真系统的参考架构[J].系统仿真学报,2011,23(4):681-686.
    [72]贺业方,朱兵,谭伟忠,等.生物质能源基地中原料供应模式选址的理论分析[J].林业经济问题,2009,29(5):382-383.
    [73]黄超,费奇.基于HLA的物流仿真系统对象模型研究[J].计算机与数字工程,2005,33(4):45-49.
    [74]嵇振平,陈文明,于戈.分层有色Petri Net (HCPN)及其在宝钢炼钢连铸生产物流系统仿真建模中的应用[J].冶金自动化,2002,27(2):6-9.
    [75]姜昌华,韩伟,胡幼华.REPAST——个多Agent仿真平台[J].系统仿真学报,2006,18(8):2319-2322.
    [76]姜金菊,林杰.基于智能代理的供应链仿真[J].系统仿真学报,2004,16(12):2847-2850.
    [77]金淳,王刚,高鹏.HLA在供应链仿真中的应用研究综述[J].系统仿真学报,2008,20(4):817-822,909.
    [78]鞠儒生,乔海泉,陈少卿,等.一种新型HLA仿真结果处理方法[J].计算机仿真,2006,23(6):143-146.
    [79]黎继,李柏勋,刘春玲.基于系统动力学仿真的集群式供应链跨链间库存管理[J].系统工程,2007,25(7):25-32.
    [80]李伯虎,刘青.一个基于面向对象技术的车间调度仿真软件[J].系统仿真学报,1995,7(3):1-8.
    [81]李剑锋,陈燕,翟军,等.港口供应链系统动力仿真模型研究[J].计算机工程与应用,2010,46(35):18-21.
    [82]林杰,冯凌,尤建新.基于Agent的供应链运作仿真技术的研究[J].工业工程与管理,2005,(4):41-44.
    [83]林雅慧,钟晓燕,钟聪儿,等.基于遗传算法的木材物流中心选址研究[J].运筹与管理,2007(6):51-56.
    [84]刘璠,聂华,郑海鹰.我国木材的贸易格局与市场策略[J].国际贸易问题,2004,(09):32-38.
    [85]刘光俊,李清,陈禹六.短生命周期产品的供应链仿真框架[J].计算机工程与应用,2002,(22):74-77.
    [86]刘俊,黄秀玲,张智光.基于产品特征向量的产品配置研究[J].制造业自动化,2008a,(12):18-21.
    [87]刘俊,黄秀玲,张智光.基于产品特征向量的产品配置知识表达[J].计算机工程,2008b,34(18):19-23.
    [88]刘俊,张智光.C/S模式管理信息系统的智能升级[J].南京林业大学学报(自然科学版),2008c,32(3):87-90.
    [89]刘希龙,季建华,李金龙.基于系统动力学仿真的供应网络组织结构[J].系统工程,2006,24(6):40-45.
    [90]龙勤,孟丽清.基于多Agent的林产品供应链管理框架构建[J].中国市场,2007b(2):98-99.
    [91]隆清琦,林杰.基于多Agent的供应链分布式仿真系统设计与实现[J].计算机应用,2009,29(9):2556-2591.
    [92]倪跃,王小平,曹立明.基于Agent的第三方物流库存决策仿真[J].计算机应用与软件,2007,24(2):16-18.
    [93]彭志高,滕春贤.基于系统动力学的供应链网络仿真模型的研究[J].哈尔滨理工大学学报,2007,12(2):153-156.
    [94]王飞,黄宁.基于网格的HLA分布式交互仿真研究与实现[J].计算机集成制造系统,2004,10(S1):17-20.
    [95]王汝传,徐小龙,黄海平.智能AGENT及其在信息网络中的应用[M].北京:北京邮电大学出版社,2006.
    [96]王涛.生物能源林未来生物燃料油原料基地[J].绿色中国,2007(5):30-33.
    [97]王文光,林杰.用于供应链运作的MAS分布式仿真平台建模研究.系统仿真学报,2009,21(19):6099-6013.
    [98]王晓松,吴燕.信息时代下我国农产品物流问题初探[J].林业经济问题,2006,26(6):553-557.
    [99]邬可义.关于森林价值平衡实现的构想[J].世界林业研究,2009,22(02):71-74.
    [100]晏春平,齐欢,吴义明.基于HLA的企业供应链管理仿真研究[J].计算机仿真,2005,22(5):248-251.
    [101]叶秋香.马尾松枝桠材木片贮存期对制浆性能的影响[J].中华纸业,2010,31(24):3-6.
    [102]余峰,齐欢,代建民.基于HLA的物流配送系统仿真[J].计算机与数字工程,2005,33(4):41-44.
    [103]詹跃东,骆瑛.基于Petri网的物流自动化系统建模与仿真研究[J].系统仿真学报,2001,13(4):501-504.
    [104]张浩.林业产业集聚与林业物流发展策略的探讨[J].物流技术,2009(9):25-27.
    [105]张和明,王宏伟,贾丽.基于Web服务和HLA的分布式建模与仿真环境[J].系统仿真学报,2006,18(S2):343-346.
    [106]张晴,刘志学.基于多agent的供应链信息协调建模与仿真[J].计算机应用研究,2009,26(10):3709-3711.
    [107]张涛,谭跃进,武小悦.基于有色广义随机Petri网的虚拟供应链仿真方法[J].计算机仿真,2003,20(11):100-102.
    [108]张维勇,梅勃,钱军,等.基于多智能代理的供应链仿真模型的构建[J].计算机应用,2007,27(6):99-101.
    [109]张智光.林业产业管理的新动态:林业绿色供应链[J].林业经济,2008(12):57-62.
    [110]张智光.林纸一体化绿色供应链系统的结构与特性分析[J].南京林业大学学报(人文社会科学版),2009,9(4):69-75.
    [111]张智光.绿色供应链视角下的林纸一体化共生机制[J].林业科学,2011a,47(2):111-117.
    [112]张智光.绿色共生型供应链模式——林纸一体化的发展趋势(“十一五”国家科技支撑计划项目“林纸一体化运行模式研究与示范”课题成果介绍)[J].造纸信息,2011b(12):19-21.
    [113]张智光,刘俊,杨加猛,等.绿色中国(第三卷):绿色共生模式的运用[M].北京:中国环境科学出版社,2011c.
    [114]张智光.林纸循环经济系统的资源、生态和价值链拓展模型[J].中国人口资源与环境,2012a,22(12):46-53.
    [115]张智光,姚惠芳.造纸工业循环经济的绿色共生特性和5R模式研究[J].东南大学学报(哲学社会科学版),2012,14(4):29-35.
    [116]周庆,甘仞初.供应链配送系统的多主体Petri网模型的建模方法探索[J].北京理工大学学报,2002,12:786-790.
    [117]周庆,陈剑.基于Swarm的供应链多主体聚集模型及其仿真[J].系统仿真学报,2004,16(6):1308-1313.
    [118]周庆,陈剑.基于Swarm的供应链运作模型的仿真研究[J].系统仿真学报,2008,20(16):4398-4403.
    [119]周彦,戴剑伟.HLA仿真程序设计[M].北京:电子工业出版社,2002.
    [120]朱永林,栗田奎.谈如何加强木材产品物流管理水平[J].森林工程,2003,19(1):23-24.

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