集装箱空箱调运优化的模型与方法研究
|
摘要
随着全球经济的一体化,集装箱运输在经济贸易中所体现出来的重要性越来越显著,伴随着集装箱运输的飞速发展,集装箱空箱调运问题也日益突出。
关于空箱调运的问题已引起了众多学者的重视,并进行了相应的研究,但就目前的研究水平来看,目前仍处在定性研究阶段,针对空箱调运问题的系统化的、严谨的定量分析目前在国内外文献上鲜有发表。航运公司也大都还沿用经验调度的方式,在没有相应的调箱优化系统支持的情况下,仅仅凭经验要做到科学、合理的调箱非常困难。
随着集装箱运输实践的深入和时间的推移,提出更加符合实际集装箱运输网络的空箱调运的理论、模型和方法将是十分必要的,且对于整个ITS的发展有着深远的理论和实践意义。
本论文从航运公司的角度出发,借鉴火车的空车调度,将定量分析与定性分析相结合,力图建立科学、合理的空箱调运优化模型,实现空箱调运地点、数量和时间上的最优化。全文的主要研究内容如下:
(1)从集装箱的流转过程入手,对空箱调运系统进行了界定,将空箱调运问题分为陆上的空箱调运及海上的空箱调运,并分别从系统的构成、空箱的需求及供应的角度对它们进行分析,建立了以运输费用最小为目标的混合整数规划模型,同时,结合实例对空箱调运的费用进行了详细的分析;
(2)分析了实际调运中经常遇到的不确定条件下空箱调运问题。针对陆上空箱调运系统内存在随机性需求的情况建立了机会约束空箱调运模型,探讨了目标函数中含有随机参数的空箱调运模型的求解方法,提出了两阶段随机模拟的遗传算法对调运模型进行求解,通过仿真分析,并与确定性条件下的空箱调运结果进行了对比,表明了模型求解的可行性,符合客观调度实际,为探讨随机陆上空箱调运问题提供了新的思路;
(3)将时间窗的特点引入集装箱空箱调运问题中,研究了带时间窗的集装箱空箱调运问题,即当集装箱发送时间有具体限制条件下,如何合理调度空箱的问题。所建立的带有软、硬时间窗的空箱调运的混合整数规划模型符合客观实际,并首次采用免疫算法进行求解,仿真试验表明,该算法能较好解决这一带有复杂约束条件的空箱调运问题,为集装箱空箱调运模型的求解探寻了新的方法;
(4)研究了比陆运空箱调运系统更加复杂的海运空箱调运系统,在现有研究成果基础上,对应用Petri网研究海运空箱调运问题进行了的探讨,对长期以来困扰航运公司的空箱调运问题进行了定量分析。建立了基于Petri网的海运集装箱空箱调运模型,提出了遗传算法和Petri网相结合的海运空箱调运求解方法。该方法克服了单一Petri网模型优化处理的局限性和复杂性,充分发挥了Petri网和遗传算法各自的优势和互补作用,使Petri网模型和遗传算法快速求解的优势得到发挥。通过对某航运公司中某航区内基本港间的空箱调运过程的仿真分析表明,应用遗传算法和Petri网对海运空箱调运系统进行仿真求解是可行的,可以快速、合理地确定空箱调运最优的数量、地点以及时间,具有一定的实用参考价值,值得深入研究;
(5)充分考虑了客户的不同需求,将集装箱空箱调运问题归结为如何在满足客户需求的基础上通过确定合理的运输方式和运输路径以使总费用最小化。根据调运实际,分析总结了影响客户满意度的因素,并将其归结为6个指标(即及时、快速、准时、方便、经济、适合)。建立了基于客户满意度的空箱调运模型,同时,将灰色评价理论和广义费用的概念相结合,提出依据满意度指标将原费用矩阵转化为广义费用矩阵来确定基于客户满意度的空箱调运方案的方法,该方法能够满足不同客户的特殊要求,自适应地为客户提供最优调运方式,从而,从营销的角度分析了航运企业在愈加激烈的竞争中需要转化经营理念,以增强其竞争力;
(6)结合人工智能、Agent模式和集装箱动态跟踪系统的发展,提出了把多Agent模式应用于空箱调运决策系统中,可以在满足在重箱运输需求下,进行多目标的空箱调运优化。提出了基于MAS的空箱调运分层递阶控制系统,该系统具有分层的信息处理和决策机构,可以改善系统各组成部分的协作能力和主动性,提高整个空箱调运系统的决策能力,对集装箱多式联运的发展具有重要的意义。
With the globalization of economy, it is more and more obvious that container transportation plays an important role in the world trade. Along with this development,the empty reposition becomes barrier of developing further.
This barrier arouses many scholars’interest, and they proceed homologous research. But reviewing the current researching, the study of reposition optimization is still placed in the stage of determining the nature, there are seldom literatures which is dead against systematical and precise quantitative analysis. Shipping company still distributes the empties with the experience. Therefore, it is very difficult to operate economically without mathematics model of reposition.
Along with the container transportation development, it is necessary to put forward theory, model and method to match the current transportation net’s development. Furthermore, it is helpful to the development of ITS.
From the angle of the shipping company and using the empty car distribution theories for reference, the optimization model which combined the qualitative analysis and the quantitative analysis is constructed for empty reposition , so that the optimization of routing, quantity and time is available. The contents and innovative points of this dissertation include:
(1)Through studying the procedure of container delivery, the whole systems of empty reposition is assorted of the land-reposition and the sea-reposition. According to the component of this system, the demand and supply of empties, the homologous mathematics model which can minimize the transportation cost is constructed. Simultaneously, .the cost of reposition is analysed with the real example.
(2)Analysing the reposition with unconcerned situation and the random requirement in the land-reposition, a chance constrained model is constructed. On the same time, the strategy of the reposition model which comprises random parameter is found. Within the research, GA of stochastic simulation in two phases to resolve is used. According to the simulation analysis and compare with the data that get from the reposition with certain situation, the model is available. So this model provides new strategy to the empty reposition.
(3)The reposition model with time-window is used into resolving the reposition, which can resolve the problem of reasonable reposition with concrete restricting term of launching time. This model with time restriction is accordant with the fact. It is the first using immune algorithm to solve this model. The following simulation shows this algorithm can solve the reposition with complex restriction.
(4)Researching the system of sea-reposition which is more complex than land-reposition, how to usePetri net into the reposition is discussed. Therefore, the reposition which troubles shipping company long time can be researched with quantitative analysis. The reposition model which is based on Petri net is constructed and can be resolved with genetic algorithm and Petri net. This method overcomes the limitation and complication of Petri net, and makes the most use of GA and Petri net.The procedure of a certain shipping company’s reposition among its base ports is simulated, which shows that it is feasible to use Petri net and GA to research this problem. This method is useful because it can construct model easily and simply, so that it is worth to research further.
(5)Considering the clients’different demand, the problem of reposition is reduced as the cost minimization which is based on the clients’demand through choosing the reasonable routing and transportation mode. The factor which can infect the clients’satisfaction is analysed and introduced as 6 indexes. The empties reposition model which is based on the customer satisfaction through using gray system theory is constructed. On the same time, this model combines the gray system and generalized cost matrix and provides a new way which depend on the indexes. This way can satisfy with different clients and different requirement and provide the reposition optimization.
(6)With the development of artificial intelligence, Agent mode and container tracking system, it is the first time to use multi-Agent mode in the decision-making system of reposition. Since the reposition is the object with the logical and physical discrete character, the automatic adaptive cooperative multi-agent tech is used into reposition system to match the laden container’s transportation. Since the multi- agent system has layered information handling and decision-making institution, it can improve the cooperation ability and autonomy of each part, enhance the decision-making ability of whole reposition which is important to the development of container multi-model transportation.
关于空箱调运的问题已引起了众多学者的重视,并进行了相应的研究,但就目前的研究水平来看,目前仍处在定性研究阶段,针对空箱调运问题的系统化的、严谨的定量分析目前在国内外文献上鲜有发表。航运公司也大都还沿用经验调度的方式,在没有相应的调箱优化系统支持的情况下,仅仅凭经验要做到科学、合理的调箱非常困难。
随着集装箱运输实践的深入和时间的推移,提出更加符合实际集装箱运输网络的空箱调运的理论、模型和方法将是十分必要的,且对于整个ITS的发展有着深远的理论和实践意义。
本论文从航运公司的角度出发,借鉴火车的空车调度,将定量分析与定性分析相结合,力图建立科学、合理的空箱调运优化模型,实现空箱调运地点、数量和时间上的最优化。全文的主要研究内容如下:
(1)从集装箱的流转过程入手,对空箱调运系统进行了界定,将空箱调运问题分为陆上的空箱调运及海上的空箱调运,并分别从系统的构成、空箱的需求及供应的角度对它们进行分析,建立了以运输费用最小为目标的混合整数规划模型,同时,结合实例对空箱调运的费用进行了详细的分析;
(2)分析了实际调运中经常遇到的不确定条件下空箱调运问题。针对陆上空箱调运系统内存在随机性需求的情况建立了机会约束空箱调运模型,探讨了目标函数中含有随机参数的空箱调运模型的求解方法,提出了两阶段随机模拟的遗传算法对调运模型进行求解,通过仿真分析,并与确定性条件下的空箱调运结果进行了对比,表明了模型求解的可行性,符合客观调度实际,为探讨随机陆上空箱调运问题提供了新的思路;
(3)将时间窗的特点引入集装箱空箱调运问题中,研究了带时间窗的集装箱空箱调运问题,即当集装箱发送时间有具体限制条件下,如何合理调度空箱的问题。所建立的带有软、硬时间窗的空箱调运的混合整数规划模型符合客观实际,并首次采用免疫算法进行求解,仿真试验表明,该算法能较好解决这一带有复杂约束条件的空箱调运问题,为集装箱空箱调运模型的求解探寻了新的方法;
(4)研究了比陆运空箱调运系统更加复杂的海运空箱调运系统,在现有研究成果基础上,对应用Petri网研究海运空箱调运问题进行了的探讨,对长期以来困扰航运公司的空箱调运问题进行了定量分析。建立了基于Petri网的海运集装箱空箱调运模型,提出了遗传算法和Petri网相结合的海运空箱调运求解方法。该方法克服了单一Petri网模型优化处理的局限性和复杂性,充分发挥了Petri网和遗传算法各自的优势和互补作用,使Petri网模型和遗传算法快速求解的优势得到发挥。通过对某航运公司中某航区内基本港间的空箱调运过程的仿真分析表明,应用遗传算法和Petri网对海运空箱调运系统进行仿真求解是可行的,可以快速、合理地确定空箱调运最优的数量、地点以及时间,具有一定的实用参考价值,值得深入研究;
(5)充分考虑了客户的不同需求,将集装箱空箱调运问题归结为如何在满足客户需求的基础上通过确定合理的运输方式和运输路径以使总费用最小化。根据调运实际,分析总结了影响客户满意度的因素,并将其归结为6个指标(即及时、快速、准时、方便、经济、适合)。建立了基于客户满意度的空箱调运模型,同时,将灰色评价理论和广义费用的概念相结合,提出依据满意度指标将原费用矩阵转化为广义费用矩阵来确定基于客户满意度的空箱调运方案的方法,该方法能够满足不同客户的特殊要求,自适应地为客户提供最优调运方式,从而,从营销的角度分析了航运企业在愈加激烈的竞争中需要转化经营理念,以增强其竞争力;
(6)结合人工智能、Agent模式和集装箱动态跟踪系统的发展,提出了把多Agent模式应用于空箱调运决策系统中,可以在满足在重箱运输需求下,进行多目标的空箱调运优化。提出了基于MAS的空箱调运分层递阶控制系统,该系统具有分层的信息处理和决策机构,可以改善系统各组成部分的协作能力和主动性,提高整个空箱调运系统的决策能力,对集装箱多式联运的发展具有重要的意义。
With the globalization of economy, it is more and more obvious that container transportation plays an important role in the world trade. Along with this development,the empty reposition becomes barrier of developing further.
This barrier arouses many scholars’interest, and they proceed homologous research. But reviewing the current researching, the study of reposition optimization is still placed in the stage of determining the nature, there are seldom literatures which is dead against systematical and precise quantitative analysis. Shipping company still distributes the empties with the experience. Therefore, it is very difficult to operate economically without mathematics model of reposition.
Along with the container transportation development, it is necessary to put forward theory, model and method to match the current transportation net’s development. Furthermore, it is helpful to the development of ITS.
From the angle of the shipping company and using the empty car distribution theories for reference, the optimization model which combined the qualitative analysis and the quantitative analysis is constructed for empty reposition , so that the optimization of routing, quantity and time is available. The contents and innovative points of this dissertation include:
(1)Through studying the procedure of container delivery, the whole systems of empty reposition is assorted of the land-reposition and the sea-reposition. According to the component of this system, the demand and supply of empties, the homologous mathematics model which can minimize the transportation cost is constructed. Simultaneously, .the cost of reposition is analysed with the real example.
(2)Analysing the reposition with unconcerned situation and the random requirement in the land-reposition, a chance constrained model is constructed. On the same time, the strategy of the reposition model which comprises random parameter is found. Within the research, GA of stochastic simulation in two phases to resolve is used. According to the simulation analysis and compare with the data that get from the reposition with certain situation, the model is available. So this model provides new strategy to the empty reposition.
(3)The reposition model with time-window is used into resolving the reposition, which can resolve the problem of reasonable reposition with concrete restricting term of launching time. This model with time restriction is accordant with the fact. It is the first using immune algorithm to solve this model. The following simulation shows this algorithm can solve the reposition with complex restriction.
(4)Researching the system of sea-reposition which is more complex than land-reposition, how to usePetri net into the reposition is discussed. Therefore, the reposition which troubles shipping company long time can be researched with quantitative analysis. The reposition model which is based on Petri net is constructed and can be resolved with genetic algorithm and Petri net. This method overcomes the limitation and complication of Petri net, and makes the most use of GA and Petri net.The procedure of a certain shipping company’s reposition among its base ports is simulated, which shows that it is feasible to use Petri net and GA to research this problem. This method is useful because it can construct model easily and simply, so that it is worth to research further.
(5)Considering the clients’different demand, the problem of reposition is reduced as the cost minimization which is based on the clients’demand through choosing the reasonable routing and transportation mode. The factor which can infect the clients’satisfaction is analysed and introduced as 6 indexes. The empties reposition model which is based on the customer satisfaction through using gray system theory is constructed. On the same time, this model combines the gray system and generalized cost matrix and provides a new way which depend on the indexes. This way can satisfy with different clients and different requirement and provide the reposition optimization.
(6)With the development of artificial intelligence, Agent mode and container tracking system, it is the first time to use multi-Agent mode in the decision-making system of reposition. Since the reposition is the object with the logical and physical discrete character, the automatic adaptive cooperative multi-agent tech is used into reposition system to match the laden container’s transportation. Since the multi- agent system has layered information handling and decision-making institution, it can improve the cooperation ability and autonomy of each part, enhance the decision-making ability of whole reposition which is important to the development of container multi-model transportation.
引文
1. 赵宏舟. 海运集装箱调度优化问题研究[D]. 上海海运学院研究生论文,1991,12
2. 李维斌等. 公路集装箱运输调度算法研究[J]. 中国公路学报,1995,9(1):63~71
3. Teoor Gabriel Crainic,Michel Gendreau,Pierre Dejax. Dynamic and stochastic models for the allocation of empty containers[J]. Journal of the operational research society,1992:102~126
4. White W W,Bomberawlt AM. A net work algorithm for empty freight car allocation [J]. IBM System journal,1969,15(2):147~169
5. Kaj Holmmberg,Martin Joborn,Lundgr I. Improved empty freight car distribution[J]. Transportation science,1998,32(22):163~173
6. 施欣. 集装箱海运空箱调运优化分析[J]. 系统工程理论与实践,2003,4(4):70～76
7. 周红梅,方芳. 航运集装箱空箱调运优化模型的研究[J]. 武汉理工大学学报,2003,6:384~387
8. Shen W S,Khong C M. A DSS for empty container distribution planning[J]. Decision Support System,1995,15(l):75~82
9. Sook Tying Choong,Michael H.Coleb,Erhan Kutanoglu. Empty container management for intermodal transportation networks[J]. Transportation Research Part E,2002 (38):423~438
10. 吴永福, 杨家其. 港口集装箱运输与多式联运[M]. 北京人民交通出版社,1998
11. 刘鼎铭. 集装箱运输学[M]. 上海海运学院,1996 年
12. 云俊 . 运输问题优化方法的综合应用 [J]. 武汉理工大学学报 ( 交通科学与工程版 ) ,2001(3):323~325
13. 徐绪松等. 信息技术创造企业竞争优势[J]. 管理信息系统,1999(10):10~13
14. 王峥,张列平. 供应链与现代管理思想[J]. 管理信息系统,2000(2):5~7
15. Andel,Tom,Make connections in the chain[J]. Transportation and distribution,1997,38(l):43~52,Jan.
16. 邹俊善. 现代港口经济学[M]. 人民交通出版社,1997 年
17. 杨志刚. 国际集装箱多式联运实务与法规[M]. 上海科学技术出版社,1995 年 5 月
18. 徐剑华. 集装箱空箱运输的原因、现状及对策[J]. 世界海运,1998(3):26~28
19. 刘恒江. 集装箱空箱调运分析[J]. 集装箱化,2001,(10):11~13
20. 徐剑华. 集装箱空箱运输的解决对策[J]. 集装箱运输,1998 年(3):20~21
21. 刘恒江. 集装箱空箱调运 PETRI 网模型仿真分析[D]. 上海海运学院硕士学位论文,2002 年
22. 周红梅. 集装箱空箱调运优化研究[D]. 武汉交通科技大学硕十学位论文,2003 年
23. 朱小宁. 集装箱多式联运通道规划理论与方法的研究[D]. 北方交通大学博士学位论文,2000 年
24. 胡强等. 关于集装箱门到门运输作业优化的探讨[J]. 铁道货运,1998(4):21~24
25. Larry L. Ratcliffe,B.Vinod,Fredrick T.Sparrow, Optimal Prepositioning of Empty Freight Cars[J],Simulation,1984(6):269~275
26. 宗蓓华. 港口战略管理[M]. 大连海运学院出版社,1992 年 11 月
27. 吴春雷. 航运公司集装箱配箱量问题的研究[D]. 上海海运学院研究生论文,1991.12
28. 杨华龙等. 班轮航线集装箱合理配备与使用问题[J]. 大连海事大学学报,2000,2(l):20~23
29. 沈一平. 集装箱班轮公司租箱问题的研究[D]. 上海海运学院研究生论文,1996.12
30. 赵文国. 集装箱箱务管理问题之研究[D]. 上海海运学院研究生论文,1988.12
31. 杨华龙等. 集装箱班轮航线配船优化决策研究[J]. 大连海事大学学报,1998, 22(3):50~54
32. 王平,武振业. 集装箱空箱分派系统的要素分析及目标评判[J]. 西南交通大学学报,2004,1(1):16~20
33. Beaujon G J,Turnguist M A. A model for fleet sizing and vehicle allocation[J]. Transportation science,1991,25 (l):19~45
34. Jordan W,Turnguist M.A stochastic dynamic network model for rational car distribution [J]. Transportation science,1983,17(2):123~145
35. Teoor Gabriel Crainic,Michel Gendreau,Pierre Dejax. Dynamic and stochastic models for the allocation of empty containers[J]. Journal of the Operational Research Society,1992,43(10):102~126
36. Shtnya kikuchi. Empty freight car dispatching model under freight car pool concept[J]. Transport Res-B,1985,19B(3):169~195
37. 李文权,杜文. 优化空车调配问题的数学模型[J]. 系统工程理论与实践,1998,10(10):1~5
38. Haghani A E. Rail freight transportation: a review of recent optimization models for train routing and empty car distribution[J]. J. of A dv. Trans,1987(21):142~172
39. 韩廷桂. 车站货运作业过程优化的探讨[J]. 兰州铁道学院学报,1992,11(3):120~125
40. 中华人民共和国铁道部. 铁路运输调度工作规则. 1983
41. Misra S C. Linear programmings of empty wagon disposition[J]. Rail International,1972,3(3):151~180
42. PhiliP C E and Xussman J M. Inventory model of the railroad empty car distribution Process[J]. Transportation Research Record,1977,656: 52~60
43. Mendiratta V B. A dynamic optimization model of the empty car distribution process[D]. Nothwestern University,Evanston,illinois 1981
44. Mendiratta V B, Turnquist M A. Model for management of empty freight cars[J]. Transportation Research Record,1982,838:50~55
45. Jordan W C,Turnquist M A. A stochastic dynamic model for railroad car distribution[J]. Transportation Science,1983,17(2):123~145
46. Haghani A E. Formulation and Solution of a combined train routing and makeup,and empty car distribution model[J]. Transportation Research Part B 1989,23:433~452
47. 刘海林. 用电子计算机进行铁路空车调配的探讨[J]. 铁道运输经济,1987(6):29~32
48. 汤代炎. 空车调配方案的研究一匈牙利法的一个应用[J]. 长沙铁道学院学报,1990,9(4):20~25
49. 何世伟. 铁路枢纽作业轮廊计划优化模型及算法[J]. 西南交通大学学报,1995,30(10):566~572
50. 施欣. 内陆集装箱运输环境下的空箱调运策略与租箱策略的数字仿真分析[J]. 交通运输工程学报,2002,(6):114~119
51. 贺斌. 基于机会约束规划的陆上空箱调运模型[J]. 上海海运学院研究生论文,1999,12
52. 宋洁蔚,荣冈. 运输调度中不确定性问题的研究[J]. 浙江大学学报,2003,3(2):243~248
53. 徐震浩,顾幸生. 不确定条件下具有零等待的流水车间免疫调度算法[J]. 计算机集成制造系统,2004,10(10):1247~1251
54. 方红远,邓玉梅. 水资源系统不确定性决策机会约束模型法[M]. 河海大学学报,2002,1(1):88~92
55. Yoon K .The propagation of errors in multiple-attribute decision analysis: a practical approach[J]. Journal of the operational research Society,1989,40(7):681~686
56. Sajjad Zahir M. Incorporating the uncertainty of decision judgement in the hierarchy process[J]. European journal of operational research,1991,53:206~21 6
57. Bryson N,Mobolurin A. An action learning evaluation Procedure for multiple criteria decision making Problems[J]. European journal of operational research,1996,96:379~386
58. 沈清喜,张跃,王光远. 机会约束随机规划集值模型及求解[J]. 哈尔滨建筑工程学院学报,1994,4(2):9~17
59. 刘宝碇,赵瑞清. 随机规划与模糊规划[M]. 北京:清华大学出版社
60. 丁晓东,吴让泉,邵世煌. 含有模糊和随机参数的混合机会约束规划模型[J]. 控制与决策,2002,9(5):587~590
61. Charnes A,Cooper W W. Chance-constrained Programming[J]. Management Science,1959,6(l):73~79
62. Liu B,Iwamura K. Chance constrained Programming with fuzzy parameters[J]. Fuzzy Sets & Systems,1998,94(2):227~237
63. 方述成,汪定伟.模糊数学与模糊优化[M].北京:科学出版社,1997
64. Kall P,Wallace S W . Stochastic Programming[M].New York: John Wiley & Sons,1994.
65. Iwamura K,Liu B. A genetic algorithm for chance constrained programming[J].J of Infor & Optim Sci,1996,17(2):40~47.
66. 刘大熔,贺斌,蒋良奎,余爱平. 随机(单箱种)陆上空箱调运模型[J]. 上海海运学院学报,2000,9(3):8~18
67. 汪传旭,刘大熔,贺斌. 随机条件下空箱调配模型研究[J]. 交通运输工程学报,2001,9 (3):119~122
68. 陈国良等. 遗传算法及其应用[M]. 北京:人民邮电出版社,1999.
69. 玄光男等. 遗传算法与工程设计[M]. 北京:科技出版社,2000
70. 陈建安,郭大伟,徐乃平,孙云芝. 遗传算法理论研究综述[J]. 西安电子科技大学学报,1998,6(3):363~368
71. Srinivas M,Patnaik L M. Adaptive probabilities of crossover and mutation in genetic algorithm[J]. lEEE Trans Syst Man,Cybern,1994,24(4):656~667
72. Davis L. Adaptive operator probabilities in genetic algorithms[J]. In proc 3rd Int Conf Genetic Algorithms,1989:61~69
73. Fogarty J C. Varying the probability of Mutation in Genetic Algorithms[J]. In proc3rd Int Conf Genetic Algorithms,1989:42~50
74. Whitley D,Starkweather D. Genetic II: A distributed genetic algorithm[J]. Expt J Theory,Art lntell,1990,2:189~214
75. Feng Q X,Francesco p. Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space Part I and II:Basic properties of selection and mutation[J]. IEEE Trans Neural Networks,1994,5(l):102~129
76. 陈国良等. 遗传算法及其应用[M]. 北京:人民邮电出版社,1996
77. 张宗炳. 遗传与进化[M]. 北京:人民教育出版社,1981.
78. 陈彦如,蒲云. 用遗传算法解决固定需求交通平衡分配问题[J]. 西南交通大学学报,2000,35(1):44-47
79. 姜虹,高自友.用遗传算法求解拥挤条件下的公共交通随机用户平衡配流模型[J].公路交通科技,2000,17(2):30-34
80. 孙德宝,李茶玲. 遗传算法在时间最优路径规划中的应用[J]. 系统工程与电子技术,2000,
22(7):78-81
81. 王以直,张志强,李敏强. 杂合遗传算法与计算智能[J]. 系统工程理论与实践,1999 (3):53-57
82. 牛惠民. 一类带有随机参数的交通优化模型及遗传算法[J]. 系统工程学报,2002,4(2):103~108
83. 熊红云,鲁五一,温红艳. 铁路空车调配问题的遗传启发算法[J]. 中国铁道科学,2002,23(4):118~121
84. 张得志,谢如鹤,黄孝章. 铁路集装箱空箱调度模型及求解算法[J]. 中国铁道科学,2003,6(3):125~129
85. 高明霞,杨涛,张春民. 带时间窗的随机需求车辆路线问题的模型研究[J]. 兰州交通大学学报,2004,6(3):4~7
86. 宋洁蔚,荣冈. 成品油配送中时间窗的确定及运输的安排[J]. 系统工程理论与实践,2003,4:63~81
87. 袁庆达,杜文,周再玲. 带软时间窗的混合车队车辆路线问题的模型和算法研究[J]. 西南交通大学学报,2001,4:401~406
88. 胡朝阳,文福拴. 免疫算法与其它模拟进化优化算法的比较研究[J]. 电力情报,1998,61-63
89. Chun Jang-Sung ,Jang Hyun-kyo,Hahn Song-Yop. A study on comparison of optimization performances between immune algorithm and other heuristic algorithms[J]. IEEE Transaction on Magnetics,1998,34(5):2972-2975
90. Ge Hong,ao Zong-Yuan. Immune Algorithm[C]. 2001 IEEE, Proceedings of the 4th World Congress on Intelligent Control and Automation,1784~1788
91. Chun Jang-Sung,Kim Min-Kyu,Jang Hyun-kyo. Shape optimization of electromagnetic devices using immune algorithm[J]. IEEE Transaction on Magnetics,1997,33(2):1876-1879
92. 夏利民,谷士文,孙星明. 基于免疫算法的立体匹配[J]. 计算机工程,2001,27(5):3~4
93. 曹先彬,刘克胜,王煦法. 基于免疫遗传算法的装箱问题求解[J]. 小型微型计算机系统,2000,21(4):361-363
94. 刘克胜,曹先彬,郑浩然等. 基于免疫算法的TSP问题求解[J].计算机工程,2000,26(1):1~2
95. 孙勇智,韦巍. 基于人工免疫算法的电力系统最优潮流计算[J]. 电力系统自动化,2002,26(12):30-34
96. 张韵农,何振亚,蔚承建等. 图像增强的自适应免疫算法[J].东南大学学报,2002,32(3):346-350
97. 葛红. 免疫算法综述[J].华南师范大学学报,2002,8(3):120~126
98. Cheung,R.K.,Chen,C. .A two-stage stochastic network model and solution methods for the dynamic empty container allocation problem[J]. Transportation Science,1998,32(2):142~162
99. Choong , S. Container management for multimodal transportation networks[D]. M.S.Thesis ,Department of Industrial Engineering,University of Arkansas,Fayetteville,AR. 2000
100. Choong,S. Cole,M.H.,Kutanoglu,E.. Empty container management for container-on-Barge(COB) Transportation:Planning horizon effects on empty container management in a multi-modal transportation network[D]. Technical Report MBTC-2003,Mack-Blackwell Transportation Center,University of Arkansas,Fayetteville,AR. 2001
101. Crainic,T.G.,Dejax,P.,Delorme,L.. Models for multimode multicommodity location problems with interdepot balancing requirements[J]. Annals of Operations Research,1989(18): 279~302
102. Crainic,T.G.,Gendreau,M.,Dejax,P.. Dynamic and stochastic models for the allocation of empty containers[J]. Operations Research,1993,41(l):102~126
103. Dejax,P.,Benamar,F.,Crainic,T.G.,Gendreau,M. Short term container fleet management:issues, models and tools[J]. In: Proceedings of the 6th World Conference on Transport Research,Lyon,France,1992,29 June~3 July
104. De Matta,R.,Guignard,M. The Performance of rolling production schedules in a process industry[J]. IIE Transactions,1995(27):564~573
105. Florez,H.. Empty Container Repositioning and Leasing: An optimization model[D]. Polytechnic Institute of New York,New York. 1986
106. Fourer, R. , Gay , D.M. , Kernighan , B.W. AMPL:A modeling language for mathematical programming[D]. Boyd and Fraser,Massachusetts. 1993
107. Holmberg,K.,Joborn,M.,Lundgren,J.T. Improved empty freight car distribution[J]. Transportation Science,1998,32(2):163~173
108. Russell,R.A.,Urban,T.L. Horizon extension for rolling production schedules: length and accuracyrequirements[J]. International Journal of Production Economics,1993(29):111~122
109. Trusty , K. , Malstrom , M.E. A feasibility assessment of truck-barge intermodal freight transportation[D]. MBTC FR-1079,Mack-Blackwell Transportation Center,University of Arkansas,Fayetteville,AR. 1998
110. 李文波,吴冲锋,王意冈. Petri 网分析企业组织效率的探讨[J]. 管理科学学报,1999,2(2):49~56
111. 王意冈,张肖南. 用 Petri 网研究组织结构形式[J]. 系统工程学报,1998,13(3):100~116
112. 童利忠等. 基于 Petri 网的计算机模拟研究[J]. 计算机应用研究,1999,11(11): 29~31
113. 陈永凤,费奇. Petri 网在物质调运问题中的应用[J]. 系统工程理论与实践,1998 年第 18 期
114. 宫世豪等. 基于有色 Petri 网的经营过程建模[J]. 信息与控制,2000 (2)
115. 张威,黄圣国,麻士东. 基于 Petri 网的交通运输网络最短路径算法[J]. 华北航天工业学院学报,2003,12(4):16~19
116. 吕丽民,陈火旺. 基于 Petri 网模型的主动对象的研究[J]. 计算机工程与科学,1997,(5):67~73
117. 高春华. 基于面向对象智能 Petri 网的智能单元控制系统研究[D]. 西安交通大学信息工程学院,1997
118. 王景光. 系统人力资源的 Petri 网分配模型研究[J]. 系统工程理论与实践,2001(4): 106~110
119. 王丽亚、吴智铭、张钟俊. 基于 Petri 网的离散事件系统控制理论. 上海交通大学学报,1994,5:115~120
120. 廖敏、殷国富、罗中先. 基于 Petri 网的制造资源调度工作流模型研究. 计算机集成制造系统,2004,9(9):1056~1061
121. 王文学. 用 Petri 网分析离散事件动态系统[J]. 控制与决策,1990,1(1):29~36
122. 卫军胡等. 基于赋色 Petri 网的离散事件系统矩阵模型与仿真[J]. 系统仿真学报,2001,l (l):31~39
123. 郑大钟,赵千川. 离散事件动态系统[M]. 北京:清华大学出版社,2001
124. 王维平,朱一凡等. 离散事件系统建模与仿真[M]. 国防科技大学出版社,1997 年 8 月
125. 顾启泰编著. 离散事件系统建模与仿真[M]. 清华大学出版社,1999 年 8 月
126. 顾启泰. 离散时间系统建模与仿真[M]. 北京:高等教育出版社,1999
127. 邹志红,冯允成. 离散事件系统仿真输出数据的统计分析[J]. 北京航空航天大学学报,1995,21(2):72~78
128. 蒋昌俊. Petri 网理论与方法研究综述[J]. 控制与决策,1997(11):631~636
129. 袁崇义. Petri 网原理[M]. 电子工业出版社,1998 年 4 月
130. J.L.Peterson,吴哲辉译. Petri 网理论与系统模型[M]. 徐州:中国矿业大学出版,1989.
131. 林闯. 随机 Petri 网模型的精化设计[J]. 软件学报,2000,11(1):104~109
132. Eike Best. Information flow in nets[C]. First European workshop on application and theory of Petri Nets,1990,82~89
133. G..Berthelot,C.Girault,G.Roucairol. Petri net modelling and reliability of distributed algorithms[C]. first European workshop on application and theory of Petri nets,1991,3~9
134. K.K.K.LAI,Kokin Lam and W.K.Chan. Shipping container logistics and allocation[J]. Journal of the operational research society,1995,6:687~697
135. 林闯. 随机 Petri 网和系统性能评价[M]. 清华大学出版社,2000 年 1 月第 1 版
136. W.M.P.van der Aalst. Verification of work flow nets[J]. Computing science report, 1996(26):407~425
137. Zhou M C,Dicesare F. Petri net synthesis for discrete event control of manufacturing systems[M]. Boston,MA:Kluwer,1993
138. Peteson J L. Petri net theory and the modeling of system[M]. Englewood Cliffs,NJ,Prentice Hall,1981
139. Diego A Tacconi,Frank L Lewis. A new matrix model for discrete event system,application tosimulation[J]. IEEE Control Systems,1997(8):62~71
140. Isumt,et al. System modeling and analysis using Petri nets[J]. SAMS,1998,5(l):3~25
141. Martinez J., Silva M. A simple and fast algorithm to obtain all invariants of a generalized Petri nets[D]. Application and theory of Petri nets,New York,1982
142. Girault C,Reisiy W.(Editor). Application and theory of Petri nets[D]. Containerization International,Year Book,2000
143. 施欣. 基于 Petri 网的航运业务流程的仿真优化[J]. 系统仿真学报, 2001,11(6):767~780
144. 袁群,施欣. EDI 环境下集装箱运输系统组织结构的 Petri 网模型表示及仿真[J]. 系统工程理论方法应用,2002,3(1):47~53
145. 吴恺桓,季文元,施欣. Petri 网在航运业务流程重构中的应用研究[J]. 上海海运学院学报,2001,6(2):36~40
146. 刘恒江,施欣. 基于Petri网的集装箱空箱调运仿真分析[J]. 交通运输工程学报,2002,9(3):97~102
147. 张恒巍,杜彦华,汤光明,张明清. 基于多线程的列车群 Petri 网运行模型的实现[J]. 计算机应用,2002,10(10):76~78
148. 叶阳东,贾利民. 基于对象 Petri 网的列车运行模型及仿真[J]. 系统仿真学报,2002,2(2):132~135
149. 郑锋,孙树栋,吴秀丽. 基于遗传算法和模型仿真的调度规则决策方法[J]. 计算机集成制造系统,2004,7(7):809~814
150. 喻翔,毛敏,刘建兵. 城市交通需求预测组合模型的研究[J]. 西南交通大学学报,2003,2(1): 75~79
151. 刘卫果,胡思继. 旅客交通方式选择行为的模糊机会约束规划模型[J]. 北方交通大学学报,2004,4(2):60~65
152. Charnes A,Copper W W. Chance-Constrained Programming[J]. Management science,1959,6(l):73~79
153. 黄风立,赵燕伟,华尔天. 基于满意度的模糊机会约束模型在产品设计中的应用[J]. 中国机械工程,2004,12(24):2222~2225
154. 尤军,李少远. 生产调度问题的模糊满意优化[J]. 上海交通大学学报,2003,11(11):1698~1701
155. Grigoroudis E,Siskos Y. Preference disaggregation for measuring and analyzing customer satisfaction: the MUSA method[J]. European Journal of Operational research,2002,143(l):148~170
156. 孙燕. 服务于交通流诱导系统的动态路径选择模型与方法研究[D]. 东南大学博士学位论文,2003 年
157. 徐泽水. 层次分析新标度法[J]. 系统工程理论与实践,1998,18(10):74~77
158. 邓聚龙. 灰色系统理论教程[M]. 武汉:华中理工大学出版社,1990
159. 胡笙煌. 主观指标的多层次灰色评价[J]. 系统工程理论与实践,1996,16(1):12~20
160. 罗小明等. 灰色综合评判模型[J]. 系统工程与电子技术,1994,16(9):18~26
161. Tien T. L,Chen C.K. The indirect measurement of fatigue limits of structural steel by the deterministic grey dynamic model DGDM(1,1,1) [J]. Appl Math Medelling,1997,21(10),611~619
162. 袁红斌,段成华. 集装箱动态跟踪工作流网模型的建立与实现[J]. 计算机工程,2003,6(9):93~95
163. 施欣. EDI 与航运业务流程的重构[J]. 系统工程理论与实践,2002,3(3):63~71
164. 任明仑,杨善林,朱卫东. 智能决策支持系统:研究现状与挑战[J]. 系统工程学报,2002,10(5):430~440
165. 史忠植. 智能主体及其应用[M]. 科学出版社,2000
166. 刘金馄,尔联洁. 多智能体技术应用综述[J]. 控制与决策,2001,16(2): 133~180
167. 李海刚,吴启迪. 多 Agent 系统研究综述[J]. 同济大学学报,2003,6(6):728~732
168. 杨鲲,翟永顺,刘大有. Agent 特性与分类[J]. 计算机科学,1999,26(9):30~34
169. Wooldridge M J,Jenmngs N R. Intelligent agents :Theory and practice [J]. Knowledge Engineering Review,1995,10(2):115~152
170. Russell S,Norvig P . Artificial intelligence :A modern approach[M]. Upper saddle river: Prentice Hall,1995
171. Kadar B,Monnstori L,Szelke E. An object oriented frame work for developing distributed manufacturing architecture[J]. Journal of intelligent Manufacturing,1998,9(2):173~179.
172. 董宏斌,石纯一. 移动 Agent 技术研究[J]. 计算机科学,2000,27(4):35~38
173. 曾健,周健,张喜. 空车调整专家系统的研究[J]. 铁路计算机应用,1999(4):5~7
174. 邹晟,张喜,王国旗. 基于 Agent 模式的空车调整决策系统的研究[J]. 铁路计算机应用,2003.5(5):8~11
175. 董海鹰,贾石峰,李华,范多旺. 基于多 Agent 的列车分布式智能控制研究[J]. 铁道学报,2004,10(5):61~65
176. 张杰,琚春华. 基于优先级的多 Agent 协同研究[J]. 计算机时代,2004(12):21~23
177. 董海鹰,李军,薛钧义. 列车运行过程的多 Agent 集成探讨[J]. 控制与决策,2002,17(2):203~206
178. 陈曦,傅明. 基于多 Agent 的动态路径规划方法研究[J]. 计算机工程与应用,2002(21):228~ 229
179. 郭建媛,刘军,蒋熙. 基于多 Agent 的铁路运输网分布式仿真环境的研究[J]. 计算机仿真,2004,10(10):170~173
2. 李维斌等. 公路集装箱运输调度算法研究[J]. 中国公路学报,1995,9(1):63~71
3. Teoor Gabriel Crainic,Michel Gendreau,Pierre Dejax. Dynamic and stochastic models for the allocation of empty containers[J]. Journal of the operational research society,1992:102~126
4. White W W,Bomberawlt AM. A net work algorithm for empty freight car allocation [J]. IBM System journal,1969,15(2):147~169
5. Kaj Holmmberg,Martin Joborn,Lundgr I. Improved empty freight car distribution[J]. Transportation science,1998,32(22):163~173
6. 施欣. 集装箱海运空箱调运优化分析[J]. 系统工程理论与实践,2003,4(4):70～76
7. 周红梅,方芳. 航运集装箱空箱调运优化模型的研究[J]. 武汉理工大学学报,2003,6:384~387
8. Shen W S,Khong C M. A DSS for empty container distribution planning[J]. Decision Support System,1995,15(l):75~82
9. Sook Tying Choong,Michael H.Coleb,Erhan Kutanoglu. Empty container management for intermodal transportation networks[J]. Transportation Research Part E,2002 (38):423~438
10. 吴永福, 杨家其. 港口集装箱运输与多式联运[M]. 北京人民交通出版社,1998
11. 刘鼎铭. 集装箱运输学[M]. 上海海运学院,1996 年
12. 云俊 . 运输问题优化方法的综合应用 [J]. 武汉理工大学学报 ( 交通科学与工程版 ) ,2001(3):323~325
13. 徐绪松等. 信息技术创造企业竞争优势[J]. 管理信息系统,1999(10):10~13
14. 王峥,张列平. 供应链与现代管理思想[J]. 管理信息系统,2000(2):5~7
15. Andel,Tom,Make connections in the chain[J]. Transportation and distribution,1997,38(l):43~52,Jan.
16. 邹俊善. 现代港口经济学[M]. 人民交通出版社,1997 年
17. 杨志刚. 国际集装箱多式联运实务与法规[M]. 上海科学技术出版社,1995 年 5 月
18. 徐剑华. 集装箱空箱运输的原因、现状及对策[J]. 世界海运,1998(3):26~28
19. 刘恒江. 集装箱空箱调运分析[J]. 集装箱化,2001,(10):11~13
20. 徐剑华. 集装箱空箱运输的解决对策[J]. 集装箱运输,1998 年(3):20~21
21. 刘恒江. 集装箱空箱调运 PETRI 网模型仿真分析[D]. 上海海运学院硕士学位论文,2002 年
22. 周红梅. 集装箱空箱调运优化研究[D]. 武汉交通科技大学硕十学位论文,2003 年
23. 朱小宁. 集装箱多式联运通道规划理论与方法的研究[D]. 北方交通大学博士学位论文,2000 年
24. 胡强等. 关于集装箱门到门运输作业优化的探讨[J]. 铁道货运,1998(4):21~24
25. Larry L. Ratcliffe,B.Vinod,Fredrick T.Sparrow, Optimal Prepositioning of Empty Freight Cars[J],Simulation,1984(6):269~275
26. 宗蓓华. 港口战略管理[M]. 大连海运学院出版社,1992 年 11 月
27. 吴春雷. 航运公司集装箱配箱量问题的研究[D]. 上海海运学院研究生论文,1991.12
28. 杨华龙等. 班轮航线集装箱合理配备与使用问题[J]. 大连海事大学学报,2000,2(l):20~23
29. 沈一平. 集装箱班轮公司租箱问题的研究[D]. 上海海运学院研究生论文,1996.12
30. 赵文国. 集装箱箱务管理问题之研究[D]. 上海海运学院研究生论文,1988.12
31. 杨华龙等. 集装箱班轮航线配船优化决策研究[J]. 大连海事大学学报,1998, 22(3):50~54
32. 王平,武振业. 集装箱空箱分派系统的要素分析及目标评判[J]. 西南交通大学学报,2004,1(1):16~20
33. Beaujon G J,Turnguist M A. A model for fleet sizing and vehicle allocation[J]. Transportation science,1991,25 (l):19~45
34. Jordan W,Turnguist M.A stochastic dynamic network model for rational car distribution [J]. Transportation science,1983,17(2):123~145
35. Teoor Gabriel Crainic,Michel Gendreau,Pierre Dejax. Dynamic and stochastic models for the allocation of empty containers[J]. Journal of the Operational Research Society,1992,43(10):102~126
36. Shtnya kikuchi. Empty freight car dispatching model under freight car pool concept[J]. Transport Res-B,1985,19B(3):169~195
37. 李文权,杜文. 优化空车调配问题的数学模型[J]. 系统工程理论与实践,1998,10(10):1~5
38. Haghani A E. Rail freight transportation: a review of recent optimization models for train routing and empty car distribution[J]. J. of A dv. Trans,1987(21):142~172
39. 韩廷桂. 车站货运作业过程优化的探讨[J]. 兰州铁道学院学报,1992,11(3):120~125
40. 中华人民共和国铁道部. 铁路运输调度工作规则. 1983
41. Misra S C. Linear programmings of empty wagon disposition[J]. Rail International,1972,3(3):151~180
42. PhiliP C E and Xussman J M. Inventory model of the railroad empty car distribution Process[J]. Transportation Research Record,1977,656: 52~60
43. Mendiratta V B. A dynamic optimization model of the empty car distribution process[D]. Nothwestern University,Evanston,illinois 1981
44. Mendiratta V B, Turnquist M A. Model for management of empty freight cars[J]. Transportation Research Record,1982,838:50~55
45. Jordan W C,Turnquist M A. A stochastic dynamic model for railroad car distribution[J]. Transportation Science,1983,17(2):123~145
46. Haghani A E. Formulation and Solution of a combined train routing and makeup,and empty car distribution model[J]. Transportation Research Part B 1989,23:433~452
47. 刘海林. 用电子计算机进行铁路空车调配的探讨[J]. 铁道运输经济,1987(6):29~32
48. 汤代炎. 空车调配方案的研究一匈牙利法的一个应用[J]. 长沙铁道学院学报,1990,9(4):20~25
49. 何世伟. 铁路枢纽作业轮廊计划优化模型及算法[J]. 西南交通大学学报,1995,30(10):566~572
50. 施欣. 内陆集装箱运输环境下的空箱调运策略与租箱策略的数字仿真分析[J]. 交通运输工程学报,2002,(6):114~119
51. 贺斌. 基于机会约束规划的陆上空箱调运模型[J]. 上海海运学院研究生论文,1999,12
52. 宋洁蔚,荣冈. 运输调度中不确定性问题的研究[J]. 浙江大学学报,2003,3(2):243~248
53. 徐震浩,顾幸生. 不确定条件下具有零等待的流水车间免疫调度算法[J]. 计算机集成制造系统,2004,10(10):1247~1251
54. 方红远,邓玉梅. 水资源系统不确定性决策机会约束模型法[M]. 河海大学学报,2002,1(1):88~92
55. Yoon K .The propagation of errors in multiple-attribute decision analysis: a practical approach[J]. Journal of the operational research Society,1989,40(7):681~686
56. Sajjad Zahir M. Incorporating the uncertainty of decision judgement in the hierarchy process[J]. European journal of operational research,1991,53:206~21 6
57. Bryson N,Mobolurin A. An action learning evaluation Procedure for multiple criteria decision making Problems[J]. European journal of operational research,1996,96:379~386
58. 沈清喜,张跃,王光远. 机会约束随机规划集值模型及求解[J]. 哈尔滨建筑工程学院学报,1994,4(2):9~17
59. 刘宝碇,赵瑞清. 随机规划与模糊规划[M]. 北京:清华大学出版社
60. 丁晓东,吴让泉,邵世煌. 含有模糊和随机参数的混合机会约束规划模型[J]. 控制与决策,2002,9(5):587~590
61. Charnes A,Cooper W W. Chance-constrained Programming[J]. Management Science,1959,6(l):73~79
62. Liu B,Iwamura K. Chance constrained Programming with fuzzy parameters[J]. Fuzzy Sets & Systems,1998,94(2):227~237
63. 方述成,汪定伟.模糊数学与模糊优化[M].北京:科学出版社,1997
64. Kall P,Wallace S W . Stochastic Programming[M].New York: John Wiley & Sons,1994.
65. Iwamura K,Liu B. A genetic algorithm for chance constrained programming[J].J of Infor & Optim Sci,1996,17(2):40~47.
66. 刘大熔,贺斌,蒋良奎,余爱平. 随机(单箱种)陆上空箱调运模型[J]. 上海海运学院学报,2000,9(3):8~18
67. 汪传旭,刘大熔,贺斌. 随机条件下空箱调配模型研究[J]. 交通运输工程学报,2001,9 (3):119~122
68. 陈国良等. 遗传算法及其应用[M]. 北京:人民邮电出版社,1999.
69. 玄光男等. 遗传算法与工程设计[M]. 北京:科技出版社,2000
70. 陈建安,郭大伟,徐乃平,孙云芝. 遗传算法理论研究综述[J]. 西安电子科技大学学报,1998,6(3):363~368
71. Srinivas M,Patnaik L M. Adaptive probabilities of crossover and mutation in genetic algorithm[J]. lEEE Trans Syst Man,Cybern,1994,24(4):656~667
72. Davis L. Adaptive operator probabilities in genetic algorithms[J]. In proc 3rd Int Conf Genetic Algorithms,1989:61~69
73. Fogarty J C. Varying the probability of Mutation in Genetic Algorithms[J]. In proc3rd Int Conf Genetic Algorithms,1989:42~50
74. Whitley D,Starkweather D. Genetic II: A distributed genetic algorithm[J]. Expt J Theory,Art lntell,1990,2:189~214
75. Feng Q X,Francesco p. Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space Part I and II:Basic properties of selection and mutation[J]. IEEE Trans Neural Networks,1994,5(l):102~129
76. 陈国良等. 遗传算法及其应用[M]. 北京:人民邮电出版社,1996
77. 张宗炳. 遗传与进化[M]. 北京:人民教育出版社,1981.
78. 陈彦如,蒲云. 用遗传算法解决固定需求交通平衡分配问题[J]. 西南交通大学学报,2000,35(1):44-47
79. 姜虹,高自友.用遗传算法求解拥挤条件下的公共交通随机用户平衡配流模型[J].公路交通科技,2000,17(2):30-34
80. 孙德宝,李茶玲. 遗传算法在时间最优路径规划中的应用[J]. 系统工程与电子技术,2000,
22(7):78-81
81. 王以直,张志强,李敏强. 杂合遗传算法与计算智能[J]. 系统工程理论与实践,1999 (3):53-57
82. 牛惠民. 一类带有随机参数的交通优化模型及遗传算法[J]. 系统工程学报,2002,4(2):103~108
83. 熊红云,鲁五一,温红艳. 铁路空车调配问题的遗传启发算法[J]. 中国铁道科学,2002,23(4):118~121
84. 张得志,谢如鹤,黄孝章. 铁路集装箱空箱调度模型及求解算法[J]. 中国铁道科学,2003,6(3):125~129
85. 高明霞,杨涛,张春民. 带时间窗的随机需求车辆路线问题的模型研究[J]. 兰州交通大学学报,2004,6(3):4~7
86. 宋洁蔚,荣冈. 成品油配送中时间窗的确定及运输的安排[J]. 系统工程理论与实践,2003,4:63~81
87. 袁庆达,杜文,周再玲. 带软时间窗的混合车队车辆路线问题的模型和算法研究[J]. 西南交通大学学报,2001,4:401~406
88. 胡朝阳,文福拴. 免疫算法与其它模拟进化优化算法的比较研究[J]. 电力情报,1998,61-63
89. Chun Jang-Sung ,Jang Hyun-kyo,Hahn Song-Yop. A study on comparison of optimization performances between immune algorithm and other heuristic algorithms[J]. IEEE Transaction on Magnetics,1998,34(5):2972-2975
90. Ge Hong,ao Zong-Yuan. Immune Algorithm[C]. 2001 IEEE, Proceedings of the 4th World Congress on Intelligent Control and Automation,1784~1788
91. Chun Jang-Sung,Kim Min-Kyu,Jang Hyun-kyo. Shape optimization of electromagnetic devices using immune algorithm[J]. IEEE Transaction on Magnetics,1997,33(2):1876-1879
92. 夏利民,谷士文,孙星明. 基于免疫算法的立体匹配[J]. 计算机工程,2001,27(5):3~4
93. 曹先彬,刘克胜,王煦法. 基于免疫遗传算法的装箱问题求解[J]. 小型微型计算机系统,2000,21(4):361-363
94. 刘克胜,曹先彬,郑浩然等. 基于免疫算法的TSP问题求解[J].计算机工程,2000,26(1):1~2
95. 孙勇智,韦巍. 基于人工免疫算法的电力系统最优潮流计算[J]. 电力系统自动化,2002,26(12):30-34
96. 张韵农,何振亚,蔚承建等. 图像增强的自适应免疫算法[J].东南大学学报,2002,32(3):346-350
97. 葛红. 免疫算法综述[J].华南师范大学学报,2002,8(3):120~126
98. Cheung,R.K.,Chen,C. .A two-stage stochastic network model and solution methods for the dynamic empty container allocation problem[J]. Transportation Science,1998,32(2):142~162
99. Choong , S. Container management for multimodal transportation networks[D]. M.S.Thesis ,Department of Industrial Engineering,University of Arkansas,Fayetteville,AR. 2000
100. Choong,S. Cole,M.H.,Kutanoglu,E.. Empty container management for container-on-Barge(COB) Transportation:Planning horizon effects on empty container management in a multi-modal transportation network[D]. Technical Report MBTC-2003,Mack-Blackwell Transportation Center,University of Arkansas,Fayetteville,AR. 2001
101. Crainic,T.G.,Dejax,P.,Delorme,L.. Models for multimode multicommodity location problems with interdepot balancing requirements[J]. Annals of Operations Research,1989(18): 279~302
102. Crainic,T.G.,Gendreau,M.,Dejax,P.. Dynamic and stochastic models for the allocation of empty containers[J]. Operations Research,1993,41(l):102~126
103. Dejax,P.,Benamar,F.,Crainic,T.G.,Gendreau,M. Short term container fleet management:issues, models and tools[J]. In: Proceedings of the 6th World Conference on Transport Research,Lyon,France,1992,29 June~3 July
104. De Matta,R.,Guignard,M. The Performance of rolling production schedules in a process industry[J]. IIE Transactions,1995(27):564~573
105. Florez,H.. Empty Container Repositioning and Leasing: An optimization model[D]. Polytechnic Institute of New York,New York. 1986
106. Fourer, R. , Gay , D.M. , Kernighan , B.W. AMPL:A modeling language for mathematical programming[D]. Boyd and Fraser,Massachusetts. 1993
107. Holmberg,K.,Joborn,M.,Lundgren,J.T. Improved empty freight car distribution[J]. Transportation Science,1998,32(2):163~173
108. Russell,R.A.,Urban,T.L. Horizon extension for rolling production schedules: length and accuracyrequirements[J]. International Journal of Production Economics,1993(29):111~122
109. Trusty , K. , Malstrom , M.E. A feasibility assessment of truck-barge intermodal freight transportation[D]. MBTC FR-1079,Mack-Blackwell Transportation Center,University of Arkansas,Fayetteville,AR. 1998
110. 李文波,吴冲锋,王意冈. Petri 网分析企业组织效率的探讨[J]. 管理科学学报,1999,2(2):49~56
111. 王意冈,张肖南. 用 Petri 网研究组织结构形式[J]. 系统工程学报,1998,13(3):100~116
112. 童利忠等. 基于 Petri 网的计算机模拟研究[J]. 计算机应用研究,1999,11(11): 29~31
113. 陈永凤,费奇. Petri 网在物质调运问题中的应用[J]. 系统工程理论与实践,1998 年第 18 期
114. 宫世豪等. 基于有色 Petri 网的经营过程建模[J]. 信息与控制,2000 (2)
115. 张威,黄圣国,麻士东. 基于 Petri 网的交通运输网络最短路径算法[J]. 华北航天工业学院学报,2003,12(4):16~19
116. 吕丽民,陈火旺. 基于 Petri 网模型的主动对象的研究[J]. 计算机工程与科学,1997,(5):67~73
117. 高春华. 基于面向对象智能 Petri 网的智能单元控制系统研究[D]. 西安交通大学信息工程学院,1997
118. 王景光. 系统人力资源的 Petri 网分配模型研究[J]. 系统工程理论与实践,2001(4): 106~110
119. 王丽亚、吴智铭、张钟俊. 基于 Petri 网的离散事件系统控制理论. 上海交通大学学报,1994,5:115~120
120. 廖敏、殷国富、罗中先. 基于 Petri 网的制造资源调度工作流模型研究. 计算机集成制造系统,2004,9(9):1056~1061
121. 王文学. 用 Petri 网分析离散事件动态系统[J]. 控制与决策,1990,1(1):29~36
122. 卫军胡等. 基于赋色 Petri 网的离散事件系统矩阵模型与仿真[J]. 系统仿真学报,2001,l (l):31~39
123. 郑大钟,赵千川. 离散事件动态系统[M]. 北京:清华大学出版社,2001
124. 王维平,朱一凡等. 离散事件系统建模与仿真[M]. 国防科技大学出版社,1997 年 8 月
125. 顾启泰编著. 离散事件系统建模与仿真[M]. 清华大学出版社,1999 年 8 月
126. 顾启泰. 离散时间系统建模与仿真[M]. 北京:高等教育出版社,1999
127. 邹志红,冯允成. 离散事件系统仿真输出数据的统计分析[J]. 北京航空航天大学学报,1995,21(2):72~78
128. 蒋昌俊. Petri 网理论与方法研究综述[J]. 控制与决策,1997(11):631~636
129. 袁崇义. Petri 网原理[M]. 电子工业出版社,1998 年 4 月
130. J.L.Peterson,吴哲辉译. Petri 网理论与系统模型[M]. 徐州:中国矿业大学出版,1989.
131. 林闯. 随机 Petri 网模型的精化设计[J]. 软件学报,2000,11(1):104~109
132. Eike Best. Information flow in nets[C]. First European workshop on application and theory of Petri Nets,1990,82~89
133. G..Berthelot,C.Girault,G.Roucairol. Petri net modelling and reliability of distributed algorithms[C]. first European workshop on application and theory of Petri nets,1991,3~9
134. K.K.K.LAI,Kokin Lam and W.K.Chan. Shipping container logistics and allocation[J]. Journal of the operational research society,1995,6:687~697
135. 林闯. 随机 Petri 网和系统性能评价[M]. 清华大学出版社,2000 年 1 月第 1 版
136. W.M.P.van der Aalst. Verification of work flow nets[J]. Computing science report, 1996(26):407~425
137. Zhou M C,Dicesare F. Petri net synthesis for discrete event control of manufacturing systems[M]. Boston,MA:Kluwer,1993
138. Peteson J L. Petri net theory and the modeling of system[M]. Englewood Cliffs,NJ,Prentice Hall,1981
139. Diego A Tacconi,Frank L Lewis. A new matrix model for discrete event system,application tosimulation[J]. IEEE Control Systems,1997(8):62~71
140. Isumt,et al. System modeling and analysis using Petri nets[J]. SAMS,1998,5(l):3~25
141. Martinez J., Silva M. A simple and fast algorithm to obtain all invariants of a generalized Petri nets[D]. Application and theory of Petri nets,New York,1982
142. Girault C,Reisiy W.(Editor). Application and theory of Petri nets[D]. Containerization International,Year Book,2000
143. 施欣. 基于 Petri 网的航运业务流程的仿真优化[J]. 系统仿真学报, 2001,11(6):767~780
144. 袁群,施欣. EDI 环境下集装箱运输系统组织结构的 Petri 网模型表示及仿真[J]. 系统工程理论方法应用,2002,3(1):47~53
145. 吴恺桓,季文元,施欣. Petri 网在航运业务流程重构中的应用研究[J]. 上海海运学院学报,2001,6(2):36~40
146. 刘恒江,施欣. 基于Petri网的集装箱空箱调运仿真分析[J]. 交通运输工程学报,2002,9(3):97~102
147. 张恒巍,杜彦华,汤光明,张明清. 基于多线程的列车群 Petri 网运行模型的实现[J]. 计算机应用,2002,10(10):76~78
148. 叶阳东,贾利民. 基于对象 Petri 网的列车运行模型及仿真[J]. 系统仿真学报,2002,2(2):132~135
149. 郑锋,孙树栋,吴秀丽. 基于遗传算法和模型仿真的调度规则决策方法[J]. 计算机集成制造系统,2004,7(7):809~814
150. 喻翔,毛敏,刘建兵. 城市交通需求预测组合模型的研究[J]. 西南交通大学学报,2003,2(1): 75~79
151. 刘卫果,胡思继. 旅客交通方式选择行为的模糊机会约束规划模型[J]. 北方交通大学学报,2004,4(2):60~65
152. Charnes A,Copper W W. Chance-Constrained Programming[J]. Management science,1959,6(l):73~79
153. 黄风立,赵燕伟,华尔天. 基于满意度的模糊机会约束模型在产品设计中的应用[J]. 中国机械工程,2004,12(24):2222~2225
154. 尤军,李少远. 生产调度问题的模糊满意优化[J]. 上海交通大学学报,2003,11(11):1698~1701
155. Grigoroudis E,Siskos Y. Preference disaggregation for measuring and analyzing customer satisfaction: the MUSA method[J]. European Journal of Operational research,2002,143(l):148~170
156. 孙燕. 服务于交通流诱导系统的动态路径选择模型与方法研究[D]. 东南大学博士学位论文,2003 年
157. 徐泽水. 层次分析新标度法[J]. 系统工程理论与实践,1998,18(10):74~77
158. 邓聚龙. 灰色系统理论教程[M]. 武汉:华中理工大学出版社,1990
159. 胡笙煌. 主观指标的多层次灰色评价[J]. 系统工程理论与实践,1996,16(1):12~20
160. 罗小明等. 灰色综合评判模型[J]. 系统工程与电子技术,1994,16(9):18~26
161. Tien T. L,Chen C.K. The indirect measurement of fatigue limits of structural steel by the deterministic grey dynamic model DGDM(1,1,1) [J]. Appl Math Medelling,1997,21(10),611~619
162. 袁红斌,段成华. 集装箱动态跟踪工作流网模型的建立与实现[J]. 计算机工程,2003,6(9):93~95
163. 施欣. EDI 与航运业务流程的重构[J]. 系统工程理论与实践,2002,3(3):63~71
164. 任明仑,杨善林,朱卫东. 智能决策支持系统:研究现状与挑战[J]. 系统工程学报,2002,10(5):430~440
165. 史忠植. 智能主体及其应用[M]. 科学出版社,2000
166. 刘金馄,尔联洁. 多智能体技术应用综述[J]. 控制与决策,2001,16(2): 133~180
167. 李海刚,吴启迪. 多 Agent 系统研究综述[J]. 同济大学学报,2003,6(6):728~732
168. 杨鲲,翟永顺,刘大有. Agent 特性与分类[J]. 计算机科学,1999,26(9):30~34
169. Wooldridge M J,Jenmngs N R. Intelligent agents :Theory and practice [J]. Knowledge Engineering Review,1995,10(2):115~152
170. Russell S,Norvig P . Artificial intelligence :A modern approach[M]. Upper saddle river: Prentice Hall,1995
171. Kadar B,Monnstori L,Szelke E. An object oriented frame work for developing distributed manufacturing architecture[J]. Journal of intelligent Manufacturing,1998,9(2):173~179.
172. 董宏斌,石纯一. 移动 Agent 技术研究[J]. 计算机科学,2000,27(4):35~38
173. 曾健,周健,张喜. 空车调整专家系统的研究[J]. 铁路计算机应用,1999(4):5~7
174. 邹晟,张喜,王国旗. 基于 Agent 模式的空车调整决策系统的研究[J]. 铁路计算机应用,2003.5(5):8~11
175. 董海鹰,贾石峰,李华,范多旺. 基于多 Agent 的列车分布式智能控制研究[J]. 铁道学报,2004,10(5):61~65
176. 张杰,琚春华. 基于优先级的多 Agent 协同研究[J]. 计算机时代,2004(12):21~23
177. 董海鹰,李军,薛钧义. 列车运行过程的多 Agent 集成探讨[J]. 控制与决策,2002,17(2):203~206
178. 陈曦,傅明. 基于多 Agent 的动态路径规划方法研究[J]. 计算机工程与应用,2002(21):228~ 229
179. 郭建媛,刘军,蒋熙. 基于多 Agent 的铁路运输网分布式仿真环境的研究[J]. 计算机仿真,2004,10(10):170~173