大规模定制下基于约束的产品配置方法研究
|
摘要
大规模定制(MC)的目的是以大规模生产的效率和成本向用户提供定制产品或服务。产品配置技术是MC实施的重要支撑工具。它的使用有助于企业提高获取客户定单的效率,缩短产品设计的时间和生产提前期,减少在制品和成品的库存,增加对生产过程的控制,提高客户对定制产品的满意度。
论文通过对大规模定制的概念、本质属性详细分析,结合可配置产品的概念、特点与优势,指出以可配置产品为基础组织企业的生产经营,能够集成大规模生产与传统单件定做生产的优势,使得企业在客户导向的市场环境下,有效地实施大规模定制生产。
论文针对可配置产品的复杂度的不同,提出了三种不同类型的、具有内在联系的约束满足问题理论模型,分别建模并求解复杂性程度为低、中、高的三类产品配置问题。
第一种是基于非二元约束满足问题(NCSP)的产品配置方法。提出了求解NCSP的1种非二元回溯算法和5种不同类型的非二元前向约束传播算法,并通过仿真实验对它们的求解性能进行了比较和分析;建立了基于NCSP的产品配置方法,并通过可配置汽车产品案例的仿真,说明该方法能够对产品配置中存在的非二元约束知识进行直接、自然地表示,同时能够对所建立的产品配置模型进行直接有效的求解,是一种适合于处理复杂度较低的配置问题的产品配置方法。
第二种是基于多元条件约束满足问题(NCCSP)的产品配置方法。提出了一种多元条件约束满足问题理论模型,并给出了求解NCCSP的1种回溯算法和5种不同类型的前向约束传播算法,通过计算机数据实验分析了这些算法的相关求解性能;建立了基于NCCSP的产品配置方法,并通过可配置汽车产品案例和可配置医用监测器案例的仿真,说明该方法在保留基于非二元约束满足问题的产品配置方法的优点外,还能够直接的对动态产品配置知识进行表示,同时也能够对所建立的产品配置模型进行直接有效的求解,是一种适合于处理中等复杂程度的配置问题的产品配置方法。
第三种是基于类条件约束满足问题(GCCSP)的产品配置方法。提出了一种类条件约束满足问题理论模型,并给出了类条件约束满足问题的求解方法;建立了基于UML表示的产品配置概念模型,并提出了该产品配置概念模型转化为类条件约束满足问题的方法,构建了基于类条件约束满足问题表示的产品配置模型,并通过可配置医用监测器案例的仿真实验证明了该方法的有效性。基于GCCSP的产品配置方法在保留前两种配置方法的优点外,还能够系统地、通用地对产品配置知识进行概念化表示,并能对所建立的产品配置模型进行快速求解;是一种理想的产品配置方法,适合于对非常复杂的产品配置问题进行快速建模和求解。
三种具有内在联系的不同产品配置方法的提出,为大规模定制环境下不同复杂程度产品配置系统的快速开发,提供了方法论上的指导与依据。从而为企业快速响应客户个性化的需求,提高企业的核心竞争力,奠定了坚实的基础。
The purpose of Mass Customization (MC) is to provide the customized product or service with high efficiency and low cost of mass production. Product configuration technology is an important support tool for the implementation of MC. It can help to improve the efficiency about enterprise capturing the orders from the customers, decrease the time of product design and the lead-time for production, decrease the storage of work-in-process and finished products, increase control of production and enhance the customer satisfaction degree for customized products.
According to the analysis for the concept and essential characteristics of MC in details, in combination with the definition, characteristics and advantages of the configurable products, we can indicate that the production and operations based on configurable products can effectively combine the benefits from mass production and one-of-a-kind production in order to effectively implement the strategy of MC in the customer-oriented market environment.
Aiming at different complexities with configurable products, three different kinds of constraint satisfaction problem theory models were proposed in the thesis in order to separately deal with product configuration problems with low, middle and high complexity.
The first is the product configuration method based on Non-binary Constraint Satisfaction Problem (NCSP). One non-binary backtracking algorithm and five different kinds of non-binary forwards constraint propagation algorithms were proposed for solving NCSP, and the solving performances for those algorithms were compared and analyzed by experimental simulation. The product configuration method based on NCSP was proposed and the experimental simulation for a configurable car indicates that the product configuration method can directly and naturally represent non-binary product configuration knowledge and can also deal with the built product configuration model directly and effectively. Hence, the NCSP-based product configuration method can be used to handle with the product configuration problem with low complexity.
The second is the product configuration method based Non-binary Conditional Constraint Satisfaction Problem (NCCSP). We proposed a non-binary conditional constraint satisfaction problem model. One backtracking algorithm and 5 different kinds of forwards constraint propagation algorithms were proposed and the experimental simulations for a configurable car and a configurable hospital monitor indicate that the NCCSP-based product configuration method, on the basis of preserving the advantages of the NCSP-based product configuration method, can directly represent dynamic product configuration knowledge and can also solve the built product configuration models directly and effectively. Hence, the NCCSP-based product configuration method can be used to handle with the product configuration problem with middle complexity.
The third is the product configuration method based Generic Conditional Constraint Satisfaction Problem (GCCSP). A generic conditional constraint satisfaction problem model was proposed and the solving algorithm for the GCCSP was given in the thesis. The UML-based product configuration conceptual model was built and the transformation method for the UML-based product configuration conceptual model into GCCSP was proposed. The GCCSP-based product configuration method was proposed and the experimental simulation for a configurable hospital monitor justified the proposed method. The GCCSP-based product configuration method, on the basis of preserving the advantages of NCSP-based and NCCSP-based product configuration methods, can conveniently conceptualize all kinds of product configuration knowledge systematically and universally and can also solve the built product configuration model rapidly and effectively. Hence, the GCCSP-based product configuration method is an ideal method and can be used to handle with the product configuration problem with high complexity.
The three different product configuration methods proposed can provide the guidance of methodology for us in order to rapidly develop all kinds of complicate product configuration systems under mass customization. Hence, it is possible for enterprises to quickly respond the individual requirement and improve the core competitive advantage, which further establish the stable foundation for enterprises.
论文通过对大规模定制的概念、本质属性详细分析,结合可配置产品的概念、特点与优势,指出以可配置产品为基础组织企业的生产经营,能够集成大规模生产与传统单件定做生产的优势,使得企业在客户导向的市场环境下,有效地实施大规模定制生产。
论文针对可配置产品的复杂度的不同,提出了三种不同类型的、具有内在联系的约束满足问题理论模型,分别建模并求解复杂性程度为低、中、高的三类产品配置问题。
第一种是基于非二元约束满足问题(NCSP)的产品配置方法。提出了求解NCSP的1种非二元回溯算法和5种不同类型的非二元前向约束传播算法,并通过仿真实验对它们的求解性能进行了比较和分析;建立了基于NCSP的产品配置方法,并通过可配置汽车产品案例的仿真,说明该方法能够对产品配置中存在的非二元约束知识进行直接、自然地表示,同时能够对所建立的产品配置模型进行直接有效的求解,是一种适合于处理复杂度较低的配置问题的产品配置方法。
第二种是基于多元条件约束满足问题(NCCSP)的产品配置方法。提出了一种多元条件约束满足问题理论模型,并给出了求解NCCSP的1种回溯算法和5种不同类型的前向约束传播算法,通过计算机数据实验分析了这些算法的相关求解性能;建立了基于NCCSP的产品配置方法,并通过可配置汽车产品案例和可配置医用监测器案例的仿真,说明该方法在保留基于非二元约束满足问题的产品配置方法的优点外,还能够直接的对动态产品配置知识进行表示,同时也能够对所建立的产品配置模型进行直接有效的求解,是一种适合于处理中等复杂程度的配置问题的产品配置方法。
第三种是基于类条件约束满足问题(GCCSP)的产品配置方法。提出了一种类条件约束满足问题理论模型,并给出了类条件约束满足问题的求解方法;建立了基于UML表示的产品配置概念模型,并提出了该产品配置概念模型转化为类条件约束满足问题的方法,构建了基于类条件约束满足问题表示的产品配置模型,并通过可配置医用监测器案例的仿真实验证明了该方法的有效性。基于GCCSP的产品配置方法在保留前两种配置方法的优点外,还能够系统地、通用地对产品配置知识进行概念化表示,并能对所建立的产品配置模型进行快速求解;是一种理想的产品配置方法,适合于对非常复杂的产品配置问题进行快速建模和求解。
三种具有内在联系的不同产品配置方法的提出,为大规模定制环境下不同复杂程度产品配置系统的快速开发,提供了方法论上的指导与依据。从而为企业快速响应客户个性化的需求,提高企业的核心竞争力,奠定了坚实的基础。
The purpose of Mass Customization (MC) is to provide the customized product or service with high efficiency and low cost of mass production. Product configuration technology is an important support tool for the implementation of MC. It can help to improve the efficiency about enterprise capturing the orders from the customers, decrease the time of product design and the lead-time for production, decrease the storage of work-in-process and finished products, increase control of production and enhance the customer satisfaction degree for customized products.
According to the analysis for the concept and essential characteristics of MC in details, in combination with the definition, characteristics and advantages of the configurable products, we can indicate that the production and operations based on configurable products can effectively combine the benefits from mass production and one-of-a-kind production in order to effectively implement the strategy of MC in the customer-oriented market environment.
Aiming at different complexities with configurable products, three different kinds of constraint satisfaction problem theory models were proposed in the thesis in order to separately deal with product configuration problems with low, middle and high complexity.
The first is the product configuration method based on Non-binary Constraint Satisfaction Problem (NCSP). One non-binary backtracking algorithm and five different kinds of non-binary forwards constraint propagation algorithms were proposed for solving NCSP, and the solving performances for those algorithms were compared and analyzed by experimental simulation. The product configuration method based on NCSP was proposed and the experimental simulation for a configurable car indicates that the product configuration method can directly and naturally represent non-binary product configuration knowledge and can also deal with the built product configuration model directly and effectively. Hence, the NCSP-based product configuration method can be used to handle with the product configuration problem with low complexity.
The second is the product configuration method based Non-binary Conditional Constraint Satisfaction Problem (NCCSP). We proposed a non-binary conditional constraint satisfaction problem model. One backtracking algorithm and 5 different kinds of forwards constraint propagation algorithms were proposed and the experimental simulations for a configurable car and a configurable hospital monitor indicate that the NCCSP-based product configuration method, on the basis of preserving the advantages of the NCSP-based product configuration method, can directly represent dynamic product configuration knowledge and can also solve the built product configuration models directly and effectively. Hence, the NCCSP-based product configuration method can be used to handle with the product configuration problem with middle complexity.
The third is the product configuration method based Generic Conditional Constraint Satisfaction Problem (GCCSP). A generic conditional constraint satisfaction problem model was proposed and the solving algorithm for the GCCSP was given in the thesis. The UML-based product configuration conceptual model was built and the transformation method for the UML-based product configuration conceptual model into GCCSP was proposed. The GCCSP-based product configuration method was proposed and the experimental simulation for a configurable hospital monitor justified the proposed method. The GCCSP-based product configuration method, on the basis of preserving the advantages of NCSP-based and NCCSP-based product configuration methods, can conveniently conceptualize all kinds of product configuration knowledge systematically and universally and can also solve the built product configuration model rapidly and effectively. Hence, the GCCSP-based product configuration method is an ideal method and can be used to handle with the product configuration problem with high complexity.
The three different product configuration methods proposed can provide the guidance of methodology for us in order to rapidly develop all kinds of complicate product configuration systems under mass customization. Hence, it is possible for enterprises to quickly respond the individual requirement and improve the core competitive advantage, which further establish the stable foundation for enterprises.
引文
[1] Toffler A. Future shock. New York: Bantam Books, 1970, 45-78
[2] Davis S. From future perfect: Mass customizing. Planning Review, 1989, 17(2): 16-21
[3]但斌.大规模定制——打造21世纪企业核心竞争力.北京:科学出版社, 2004, 13-50
[4]单汨源,於永和.大规模定制产品多级神经网络成本估算方法研究.中国机械工程,2004,15(11):1004-1007
[5] Giovani Da Silveira. Mass customization:Literature review and research directions. International Journal of Production Economics, 2001,72(1): 1-13
[6]单汨源,李果,陈丹.大规模定制产品族设计方案多维物元关联评价研究.计算机集成制造系统,2006,12(7):1146-1152
[7]李占山,王涛,孙吉贵,张朝辉.产品配置器的工作机理研究,计算机应用研究, 2004, (10): 24-26
[8]王涛,李占山,孙吉贵,任键,曹旭光.产品配置的知识表示,计算机科学, 2005, 32(10): 139-142
[9]李占山,寇飞宏,欧阳丹彤,孙吉贵.产品配置器的研究进展.吉林大学学报(理学版), 2006, 44(3): 429-438
[10] Juha Tiihonen,Timo Soininen.Product configurators–Information system support for configurable products.Helsinki:Helsinki University of Technology, Technical Report TKO-B137, 1997
[11] Tiihonen J, Soininen T, Mannisto T, Sulonen R. State-of-the-practice in product configuration– a survey of 10 cases in the Finnish industry. Knowledge intensive CAD, Chapman & Hall, 1996, 95-114
[12]李伟.基于约束的产品配置方法和产品优化配置研究: [合肥工业大学博士论文].安徽:合肥工业大学机械与汽车学院, 2005
[13]王世伟.基于知识的产品配置建模、演化基于应用研究: [浙江大学博士学位论文].浙江:浙江大学机械与能源工程学院, 2003
[14] Mailharro D. A Classification and Constraint-based Framework for Configuration. AI EDAM,1998, 12(4): 383–397
[15] Mittal S, Frayman F. Towards a generic model of configuration tasks. In: Proc of the 10th International Joint Conference on Artificial Intelligence. San Mateo Morgan Kaufmann Publishers, 1989, 1395-1401
[16] Freeman P, Newell A. A model for functional reasoning in design. In: Proc of the Second IJCAI, London, 1971, 621-633
[17] McDermolt J R1. A rule-based configurer of computer systems. Artificial Intelligence, 1982, 19(1): 39-88
[18] Virginia E Barker, Dennis E O’Connor. Expert systems for configuration at Digital XCON and beyond. Communications of the ACM, 1989, 32(3): 298-318
[19] Baginsky J, McDermott J. R1 revisited: four years in the trenches. AI magazine, 1984, 5(3):21-23
[20] Brown D C. Defining configuring. Artificial Intelligent for Engineering Design, Analysis and Manufacturing, 1998, 12(4): 301-306
[21] Hwai-En Tseng, Chien-Chen Chang, Shu-Hsuan Chang. Applying case-based reasoning for product configuration in mass customization environments. Expert Systems with Application, 2005, 29: 913-925
[22] Felfernig A, Friedrich G, Jannach D, M. Stumptner, etc. Configuration Knowledge Representations for Semantic Web Applications. Artificial Intelligence in Engineering, Design, Analysis and Manufacturing, 2003, 17(2): 31–50
[23] Ardissono L, Felfernig A, Friedrich G, Goy A, et al. A Framework for the Development of personalized, distributed Web-Based Configuration Systems. AI Magazine, 2003, 24(3): 93-110
[24]高鹏,林兰芬,蔡铭,董金祥.基于本体映射的产品配置模型自动获取.计算机集成制造系统-CIMS, 2003, 9(9): 810-816
[25]王世伟,谭建荣,张树有等.产品配置模型的演化与再配置.计算机辅助设计与图形学学报, 2005, 17(2): 347-352
[26]陈珂,尹建伟,陈刚等.面向网络化制造的产品再配置模型.计算机辅助设计与图形学学报, 2005, 17(7): 1607-1614
[27] Tomi Mannisto, Hannu Peltonen, Timo Soininen, et al. Multiple abstraction levels in modelling product structures. Data&Knowledge Engineering, 2001, 36: 55-78
[28] Felfernig A, Friedrich G, Jannach D, et al. Web-based configuration of virtural private networks with multiple suppliers. In: Proc of the 7th Internation Conference on Artificial Intelligence in Design. Cambridge, 2002, 41-62
[29] Nikos Karacapilidis, Thomas Leckner. A recommenndation based framework for online product configuration. In: Proc of the 6th International Conferenceon Enterprise Information Systems(ICEIS2004). Porto, 2004, 4, 303-308
[30] Felfernig A, Friedrich G, Jannach D, et al. Intelligent support for interactive configuration of mass-customized products. In: Proc of the 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems(IEA/AIE 2001). Hungary, 2001, 746-756
[31] Heinrich M, Jungst E. A resource-based paradigm for the configuring of technical systems form modular components. In: Proc of the 7th IEEE Conference on AI Applications(CAIA), 1991, 257-264
[32] Juengst W E, Heinrich M. Using resource balancing to configure modular systems. IEEE Intelligent systems, 1998, 13(4): 50-58
[33] Gorel Hedin, Lennart Ohlsson, John McKenna. Product configuration using object oriented grammars. In: Proc of the 8th International Symposium on System Configuration Management. Brussels, 1998, 107-126
[34] Alexander Felfernig, Gerhard E Friedrich,et al. UML as domain specific language for the construction of knowledge-based configuration systems. International Journal of Software Engineering and Knowledge Engineering, 2000, 10(4): 449-469
[35] Wache H, Kamp G. Using description logic for configuration problems. www.in formatik.uni-Bremen.de /-wache/publications .html
[36] Junker U, Mailharro D. The logic of ILOG (J)configurator: Combining constraint programming with a description logic. In: Proc of the IJCAI, 2003, 13-20
[37] Balcerak K J, Dale B G. Structuring modular bills of material with usage pattern analysis. International Journal of Production Research, 1992, 30(2): 283-298
[38] Veen E A Van. Generative bill of material processing systems. Production Planning and Control, 1992, 3(3): 314-326
[39] Naken Wongvasu. Methodologies for providing rapid and effective response to request for quotation (RFQ) of mass customization products: [dissertation]. Boston: Northeastern University, 2002
[40] Carol J Romanowski. A data mining approach to forming generic bills of materials in support of variant design activities. Journal of Computing and Information Science in Engineering, 2004, 4(4): 316-328
[41] Carol J Romanowski. On comparing bills of materials a similarity distance measure for unordered trees. IEEE Transactions on Systems, Man, andCybernetics Part A: Systems and Humans, 2005, 35(2): 249-260
[42] Veen E A Van. New developments in generative BOM processing systems. Production Planning and Control, 1992, 3(3): 327-335
[43] Hegge H M H. A generic bill-of-material processor using indirect identification of products. Production Planning and Control, 1992, 3(3): 336-342
[44] Hegge H M H. Intelligent product family descriptions for business applications (production control software based upon generic bills-of-material in an assemble-to-order/make-to-stock environment): [dissertation]. Eindhoven: Eindhoven University of Technology, 1995
[45] Hegge H M H. Using hierarchical pseudo bills of material for customer order acceptance and optimal material replenishment in assemble to order manufacturing of non-modular products. International Journal of Production Economics, 2000, 66(2): 171-184
[46]王世伟,谭建荣,张树有,纪杨建.基于GBOM的产品配置研究.计算机辅助设计与图形学学报, 2004, 16(5): 655-659
[47]郝刚,吴功宜.面向大规模定制的ERP中基础数据管理的研究.计算机集成制造系统, 2005, 11(4): 520-524
[48]冯韬,但斌,兰林春,张旭梅.面向大规模定制的产品族结构与配置管理.计算机集成制造系统-CIMS, 2003, 9(3):210-213
[49]但斌,冯韬.基于GBOM的产品族结构模型和配置方法.管理学报, 2005, 2 (4): 422-425
[50]梁墚,王志强,余玉刚.基于通用物料单的ATO型供应链生产规划决策模型.天津大学学报, 2004, 37(6): 559-564
[51] Olsen K A. A generic bill of materials based on a programming language notation. In: Proc of Norsk Informatikk Konferanse. Oslo, 1995, 1-12
[52] Olsen K A, S?tre P. A Procedure-oriented generic bill of materials. Computers & Industrial Engineering, 1997, 32(1): 29-45
[53] Olsen K A. Managing product variability by virtual products. International Journal of Production Research, 1997, 35(8): 2093-2107
[54] Olsen K A. Describing products as executable programs: Variant specification in a customer-oriented environment. International Journal of Production Economics, 1998, 56(1): 495-502
[55] Olsen K A. A visual product constructor for engineer-to-order environments. In: Proc of 12th International Working Seminar on Production Economics.Austria, 2001, 1-12
[56] Olsen K A. Visualizing the construction of generic bills of material. In: Proc of Recent Advances in Visual Information Systems: 5th International Conference, VISUAL 2002 Hsin Chu. Taiwan, 2002, 1-12
[57] Soininen T, Tiihonen J, Mannisto T, Sulonen R. Towards a general ontology of configuration. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 1998, 12(4): 357-372
[58] Soininen T. An approach to knowledge representation and reasoning for product configuration tasks: [dissertation]. Finland: Helsinki University of Technology, 2000, 1-24
[59] Soininen T Niemela, Tiihonen J, Sulonen R. Representing configuration knowledge with weight constraint rules. In: Proc of the 2001 AAAI Symposium, 2001, 195-201
[60] Felfernig A, Friedrich G, Jannach D. Conceptual modeling for configuration of mass-customizable products. Artificial Intelligence in Engineering, 2001, 15(2): 165-176
[61] Felfernig A, Friedrich G, Jannach D, Zanker M. Rapid Knowledge Base Development for Product Configuration Systems using the Unified Modeling Language. Taylor and Francis, 2002, 119-138
[62] Felfernig A. Standardized Configuration Knowledge Representations as Technological Foundation for Mass Customization. IEEE Transactions on Engineering Management. 2007, 54(1): 41-56
[63]张劲松,王启富,万立,钟毅方.基于本体的产品配置建模研究.计算机集成制造系统-CIMS, 2003, 9(5): 344-350
[64]张劲松,王启付,刘清华,万立,钟毅方.基于模型的产品智能化配置研究.机械工程学报, 2003, 39(6): 128-134
[65]张劲松,薛春方,刘清华,钟毅方.面向开发链的产品智能化配置技术.中南民族大学学报(自然科学版), 2005, 24(3): 93-96
[66]吴健,陈刚,尹建伟,董金祥.基于本体的产品配置知识共享.浙江大学学报(工学版), 2004, 38(4): 478-484
[67]赵燕伟,胡坚,张国贤.基于OWL本体建模的概念产品配置.中国机械工程, 2004, 15(19): 1725-1728
[68]杨晗,尹建伟,董金祥,罗尚虎.端口-连接型产品配置知识的Java表达.计算机辅助设计与图形学学报, 2005, 17(3): 511-516
[69]尹建伟,杨晗,董金祥,罗尚虎.端口-连接型产品配置本体建立与表达.计算机集成制造系统, 2005, 11(7): 1025-1050
[70] Vei-Chung Liang, Christiaan J, Paredis J. A port ontology for conceptual design of systems. Journal of Computing and Information Science in Engineering, 2004, 4(3): 206-217
[71] Sabin D, Weigel R. Product configuration frameworks-A survey. IEEE intelligent systems, 1998, 14(3): 42-49
[72] Sabin D, Freuder E C. Configuration as composite constraint satisfaction. In: Proc of AAAI, 1996, 28-36
[73] Faltings B, Weigel R. Constraint-based knowledge representation for configuration systems. Technical report No.TR-94/59, Department D’Informatique, 1994, 1-20
[74] Eugene C Freuder, Barry O’Sullivan. Generating tradeoffs for interactive constraint-based configuration. Principles and Practice of Constraint Programming-CP. 2001, 1611-3349
[75]李伟,张孟青,刘光复.基于约束满意问题的产品配置方法.农业机械学报, 2005, 36(7): 126-130
[76] Mittal S, Falkenhainer B. Dynamic constraint satisfaction problems. In: Proc of 8th AAAI, 1990, 25-32
[77] Soininen T, Gelle E, Niemel? I. A fixpoint definition of dynamic constraint satisfaction. In: Proc of CP, 1999, 419-433
[78]李伟,刘光复.一类基于动态约束满足问题的产品配置方法.机械科学与技术. 2005, 24(4): 427-430
[79] Timo Soininen, Esther Gelle. Dynamic constraint satisfaction in configuration. AAAI workshop on configuration. Florida, 1999, 95-100
[80] Stumptner M, Friedrich G E. Generative Constraint-based Configuration of Large Technical Systems. AI EDAM, 1998, 12(4): 307-320
[81] Stumptner M. An overview of knowledge-based configuration. AI Communication, 1997, 10: 111-125
[82] Stumpertner M, Haselbock A. A generative constraint formalism for configuration problems. Advances in artificial intelligence, In: Proc of Third Congress of the Italian Association for Artificial Intelligence, AIIA-93’, 1993, 302-313
[83] Stumptner M, Friedrich G, Haselbock A. Generative constraint-based configuration of large technical systems. AI EDAM, 1998, 12: 307-320
[84] Felischandel G, Friedrich G, Haselbock A, stumptner M. Configuring largesystems using generative constraint satisfaction. IEEE Intelligence Systems and their applications, 1998, 13(4): 59-68
[85] Jianxin Jiao, Mitchell M Tseng. A methodology of developing product family architecture for mass customization. Journal of Intelligence Manufacturing. 1999, 10(1): 3-20
[86] Jeff C. Having it their way: How to successfully customize your mass product. In: Proc of the 1997 40th international conference and exhibition. Washington DC, 1997, 89-91
[87]祁国宁,顾新建,谭建荣.大批量定制技术及其应用.北京:机械工业出版社, 2003, 10-15
[88]周乐,连海佳,季建华.大规模定制模式产品定制程度分析.系统管理学报, 2007, 16(6): 685-689
[89]邵晓峰,季建华,黄培清.基于Internet的大规模定制的实施条件与运作模式.计算机集成制造系统, 2001, 7(12): 53-56
[90] Piller Frank T. Mass customization: Reflections on the state of the concept. The International Journal of Flexible Manufacturing Systems, 2004, 16: 313-334
[91] Blecker T, Abdelkafi N, Kaluza B, Kreutler G. A framwork for understanding the interdepencies between mass customization and complexity. In: Proc of the 2nd international conference on business economics, Management and Marketing. Greece, 2004, 1-15
[92] Piller Frank T, Moslein K, Stotko C. Does mass customization pay. An Economic Approach to Evaluate Customer Integration, 2004, 15(4): 435-444
[93] Tseng M M, Kjellberg T, Lu S, Lu S. Design in the new e-commerce era. Annals of the CIRP, 2003, 52(2): 509-519
[94] Pine B J, Peppers D, Rogers M. Do you want to keep Your Customers Forever. Harvard Business Review, 1995, 73(2): 103-114
[95] Chamberlin E H. Product heterogeneity and public policy. American Econmic Review, 1950, 40(2): 85-92
[96] Broekhuizen T L J, Alsem K J. Success factors for mass customization: A conceptual model. Journal of Market-Focused Management, 2002, 5(4): 309-330
[97] Franke N, Von Hippel E. Satisfying heterogeneous user needs via innovation tookits: The case of apache security software. American Demographics, 2001, 23(7): 51-55
[98] Franke N, Reisinger H. Remaining within-cluster variance: A meta-analysis of the dark side of cluster anlysis. Working Paper, Vienna University of Economics and business administration, 2003, 1-15
[99] Von Hippel E. Perspective: User toolkits for innovation. Journal of Product Innovation Management, 2001, 18(4): 247-257
[100] Pine B JⅡ, Victor B, Boyntonm A C.Making masss customization work. Harvard Business Review, 1993, 71(5): 108-119
[101] Tseng M, Du X. Design by customers of mass customization products. Annals of the CIRP, 1998, 47: 103-106
[102] Davis S. Future Perfect. Addison-Wesley Publication Company, 1987, 50-89
[103] Franke N, Piller F. Toolkits for User Innovation and Design: An exploration of user interaction and value creation. Journal of Product Innovation Management, 2004, 21(6): 401-415
[104] Pine B JⅡ, Gilmore J H. The four faces of mass customization. Harvard Business Review, 1997, 75(1): 91-101
[105] Lampel J, Minlzberg H. Customizing customization. Sloan Management Review, 1996, 38(1): 21-30
[106] Alford D Sackett, Nelder G P. Mass customization-an automotive perspective. International Journal of Production Economics, 2000, 65: 99-110
[107]邵晓峰,黄培清,季建华.大规模定制生产模式的研究.工业工程与管理, 2001, 2: 13-17
[108]祈国宁,杨青海.大规模定制生产模式综述.中国机械工程, 2004, 15(14): 1240-1245
[109] Sabin M, Freuder E C, Wallace R J. Greater efficiency for conditional constraint satisfaction. In: Proc of CP 2003: Principles and practice of constraint programming, 2003, 649-666
[110] Mouhoub M, Sukpan A. Managing conditional and composite CSPs. In: Proc of Canadian Conference on AI, 2007, 216-227
[111] Sabin Mihaela, Freuder Eugene C. Detecting and resolving inconsistency and redundancy in conditional constraint satisfaction problems. In:Web-publised papers of the CP’98 workshop on constraint problem reformulation, Pisa, 1998, 1-6
[112]刘清华,万立,王启富,陈立平.基于条件约束满意问题的产品配置研究.计算机集成制造系统, 2004, 10(11): 1332-1337
[113] Sabin M. Towards more efficient solution of conditional constraint satisfactionproblems: [dissertation]. University of New Hampshire, 2003
[114] Craenen B G W, Eiben A E, Van Hemert J I. Comparing evolutionary algorithms on binary constraint satisfaction problems. IEEE Transactions on Evolutionary Computation, 2003, 7(5): 424-444
[115] Bodirsky Manuel, Kral Daniel. Locally consistent constraint satisfaction problems with binary constraints. Lecture Notes in Computer Science, 2005, 3787: 295-306
[116]杨轻云,孙吉贵,张居阳.最大度二元约束满足问题粒子群算法.计算机研究与发展, 2006, 43(3): 436-441
[117] Aldanonda Michel, Hadi-Hamou khaled, Moynard Guillaume, Lamothe Jacques. Mass customization and configuration: Requirement analysis and constraint based modeling propositions.Integrated Computer-Aided Engineering, 2003, 10(2): 177-189
[118] Lal A. Neighborhood interchangeability for non-binary CSPs & application to databases: [dissertation]. Lincoln: University of Nebraska, 2005
[119] Bacchus Fahiem, Chen Xingquang, Van Beek Peter, Walsh Toby. Binary vs. non-binary constraints. Artificial Intelligence, 2002, 140(1-2): 1-37
[120] Samaras Nikolaos, Sterqiou Kostas. Binary encodings of non-binary constraint satisfaction problems: Algorithms and experimental results. Journal of Artificial Intelligence Research, 2005, 24(7): 641-684
[121] Bessiere C, Reqin J C. MAC and combined heuristics: Two reasons to forsake FC (and CBJ?) on hard problems. In: Proc of Principles and Practice of Constraint Programming - CP96, 1996, 61-75
[122] Bessiere C, Meseguer P, Freuder E C, Larrosa J. On forward checking for non-binary constraint satisfaction. Aritficial Intelligence, 2002, 141(1-2): 205-224
[123] Zhe Liu. Algorithms for constraint satisfaction problems(CSPs): [thesis]. Canada: University of Waterloo, 1998
[124]施伯乐,丁宝康,汪卫.数据库系统教程(第2版).北京:高等教育出版社, 2005, 70-130
[125] Esther Gelle. Solving mixed and conditional constraint satisfaction problems. Constraints, 2003, 8(2): 107-141
[126] Mittal S, Frayman F. Making partial choices in constraint reasoning problems. In: Proc of AAAI, 1987, 631-636
[127] Thomas V, Gaborit P, Aldanondo M. A specificity of CSP in design:Controlling the relevance of the variables in the problem. In: Proc of the Eleventh International Conference on Principles and Practice of Constraint Programming, 2005, 34-41
[128] Mouhoub M, Sukpan A. Managing conditional and composite CSPs. In: Proc of Canadian Conference on AI, 2007, 216-227
[129] Mouhoub M, Sukpan A. Solving conditional and composite constraint satisfaction Problems. In: Proc of the 2007 ACM Symposium on Applied Computing, 2007, 336-337
[2] Davis S. From future perfect: Mass customizing. Planning Review, 1989, 17(2): 16-21
[3]但斌.大规模定制——打造21世纪企业核心竞争力.北京:科学出版社, 2004, 13-50
[4]单汨源,於永和.大规模定制产品多级神经网络成本估算方法研究.中国机械工程,2004,15(11):1004-1007
[5] Giovani Da Silveira. Mass customization:Literature review and research directions. International Journal of Production Economics, 2001,72(1): 1-13
[6]单汨源,李果,陈丹.大规模定制产品族设计方案多维物元关联评价研究.计算机集成制造系统,2006,12(7):1146-1152
[7]李占山,王涛,孙吉贵,张朝辉.产品配置器的工作机理研究,计算机应用研究, 2004, (10): 24-26
[8]王涛,李占山,孙吉贵,任键,曹旭光.产品配置的知识表示,计算机科学, 2005, 32(10): 139-142
[9]李占山,寇飞宏,欧阳丹彤,孙吉贵.产品配置器的研究进展.吉林大学学报(理学版), 2006, 44(3): 429-438
[10] Juha Tiihonen,Timo Soininen.Product configurators–Information system support for configurable products.Helsinki:Helsinki University of Technology, Technical Report TKO-B137, 1997
[11] Tiihonen J, Soininen T, Mannisto T, Sulonen R. State-of-the-practice in product configuration– a survey of 10 cases in the Finnish industry. Knowledge intensive CAD, Chapman & Hall, 1996, 95-114
[12]李伟.基于约束的产品配置方法和产品优化配置研究: [合肥工业大学博士论文].安徽:合肥工业大学机械与汽车学院, 2005
[13]王世伟.基于知识的产品配置建模、演化基于应用研究: [浙江大学博士学位论文].浙江:浙江大学机械与能源工程学院, 2003
[14] Mailharro D. A Classification and Constraint-based Framework for Configuration. AI EDAM,1998, 12(4): 383–397
[15] Mittal S, Frayman F. Towards a generic model of configuration tasks. In: Proc of the 10th International Joint Conference on Artificial Intelligence. San Mateo Morgan Kaufmann Publishers, 1989, 1395-1401
[16] Freeman P, Newell A. A model for functional reasoning in design. In: Proc of the Second IJCAI, London, 1971, 621-633
[17] McDermolt J R1. A rule-based configurer of computer systems. Artificial Intelligence, 1982, 19(1): 39-88
[18] Virginia E Barker, Dennis E O’Connor. Expert systems for configuration at Digital XCON and beyond. Communications of the ACM, 1989, 32(3): 298-318
[19] Baginsky J, McDermott J. R1 revisited: four years in the trenches. AI magazine, 1984, 5(3):21-23
[20] Brown D C. Defining configuring. Artificial Intelligent for Engineering Design, Analysis and Manufacturing, 1998, 12(4): 301-306
[21] Hwai-En Tseng, Chien-Chen Chang, Shu-Hsuan Chang. Applying case-based reasoning for product configuration in mass customization environments. Expert Systems with Application, 2005, 29: 913-925
[22] Felfernig A, Friedrich G, Jannach D, M. Stumptner, etc. Configuration Knowledge Representations for Semantic Web Applications. Artificial Intelligence in Engineering, Design, Analysis and Manufacturing, 2003, 17(2): 31–50
[23] Ardissono L, Felfernig A, Friedrich G, Goy A, et al. A Framework for the Development of personalized, distributed Web-Based Configuration Systems. AI Magazine, 2003, 24(3): 93-110
[24]高鹏,林兰芬,蔡铭,董金祥.基于本体映射的产品配置模型自动获取.计算机集成制造系统-CIMS, 2003, 9(9): 810-816
[25]王世伟,谭建荣,张树有等.产品配置模型的演化与再配置.计算机辅助设计与图形学学报, 2005, 17(2): 347-352
[26]陈珂,尹建伟,陈刚等.面向网络化制造的产品再配置模型.计算机辅助设计与图形学学报, 2005, 17(7): 1607-1614
[27] Tomi Mannisto, Hannu Peltonen, Timo Soininen, et al. Multiple abstraction levels in modelling product structures. Data&Knowledge Engineering, 2001, 36: 55-78
[28] Felfernig A, Friedrich G, Jannach D, et al. Web-based configuration of virtural private networks with multiple suppliers. In: Proc of the 7th Internation Conference on Artificial Intelligence in Design. Cambridge, 2002, 41-62
[29] Nikos Karacapilidis, Thomas Leckner. A recommenndation based framework for online product configuration. In: Proc of the 6th International Conferenceon Enterprise Information Systems(ICEIS2004). Porto, 2004, 4, 303-308
[30] Felfernig A, Friedrich G, Jannach D, et al. Intelligent support for interactive configuration of mass-customized products. In: Proc of the 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems(IEA/AIE 2001). Hungary, 2001, 746-756
[31] Heinrich M, Jungst E. A resource-based paradigm for the configuring of technical systems form modular components. In: Proc of the 7th IEEE Conference on AI Applications(CAIA), 1991, 257-264
[32] Juengst W E, Heinrich M. Using resource balancing to configure modular systems. IEEE Intelligent systems, 1998, 13(4): 50-58
[33] Gorel Hedin, Lennart Ohlsson, John McKenna. Product configuration using object oriented grammars. In: Proc of the 8th International Symposium on System Configuration Management. Brussels, 1998, 107-126
[34] Alexander Felfernig, Gerhard E Friedrich,et al. UML as domain specific language for the construction of knowledge-based configuration systems. International Journal of Software Engineering and Knowledge Engineering, 2000, 10(4): 449-469
[35] Wache H, Kamp G. Using description logic for configuration problems. www.in formatik.uni-Bremen.de /-wache/publications .html
[36] Junker U, Mailharro D. The logic of ILOG (J)configurator: Combining constraint programming with a description logic. In: Proc of the IJCAI, 2003, 13-20
[37] Balcerak K J, Dale B G. Structuring modular bills of material with usage pattern analysis. International Journal of Production Research, 1992, 30(2): 283-298
[38] Veen E A Van. Generative bill of material processing systems. Production Planning and Control, 1992, 3(3): 314-326
[39] Naken Wongvasu. Methodologies for providing rapid and effective response to request for quotation (RFQ) of mass customization products: [dissertation]. Boston: Northeastern University, 2002
[40] Carol J Romanowski. A data mining approach to forming generic bills of materials in support of variant design activities. Journal of Computing and Information Science in Engineering, 2004, 4(4): 316-328
[41] Carol J Romanowski. On comparing bills of materials a similarity distance measure for unordered trees. IEEE Transactions on Systems, Man, andCybernetics Part A: Systems and Humans, 2005, 35(2): 249-260
[42] Veen E A Van. New developments in generative BOM processing systems. Production Planning and Control, 1992, 3(3): 327-335
[43] Hegge H M H. A generic bill-of-material processor using indirect identification of products. Production Planning and Control, 1992, 3(3): 336-342
[44] Hegge H M H. Intelligent product family descriptions for business applications (production control software based upon generic bills-of-material in an assemble-to-order/make-to-stock environment): [dissertation]. Eindhoven: Eindhoven University of Technology, 1995
[45] Hegge H M H. Using hierarchical pseudo bills of material for customer order acceptance and optimal material replenishment in assemble to order manufacturing of non-modular products. International Journal of Production Economics, 2000, 66(2): 171-184
[46]王世伟,谭建荣,张树有,纪杨建.基于GBOM的产品配置研究.计算机辅助设计与图形学学报, 2004, 16(5): 655-659
[47]郝刚,吴功宜.面向大规模定制的ERP中基础数据管理的研究.计算机集成制造系统, 2005, 11(4): 520-524
[48]冯韬,但斌,兰林春,张旭梅.面向大规模定制的产品族结构与配置管理.计算机集成制造系统-CIMS, 2003, 9(3):210-213
[49]但斌,冯韬.基于GBOM的产品族结构模型和配置方法.管理学报, 2005, 2 (4): 422-425
[50]梁墚,王志强,余玉刚.基于通用物料单的ATO型供应链生产规划决策模型.天津大学学报, 2004, 37(6): 559-564
[51] Olsen K A. A generic bill of materials based on a programming language notation. In: Proc of Norsk Informatikk Konferanse. Oslo, 1995, 1-12
[52] Olsen K A, S?tre P. A Procedure-oriented generic bill of materials. Computers & Industrial Engineering, 1997, 32(1): 29-45
[53] Olsen K A. Managing product variability by virtual products. International Journal of Production Research, 1997, 35(8): 2093-2107
[54] Olsen K A. Describing products as executable programs: Variant specification in a customer-oriented environment. International Journal of Production Economics, 1998, 56(1): 495-502
[55] Olsen K A. A visual product constructor for engineer-to-order environments. In: Proc of 12th International Working Seminar on Production Economics.Austria, 2001, 1-12
[56] Olsen K A. Visualizing the construction of generic bills of material. In: Proc of Recent Advances in Visual Information Systems: 5th International Conference, VISUAL 2002 Hsin Chu. Taiwan, 2002, 1-12
[57] Soininen T, Tiihonen J, Mannisto T, Sulonen R. Towards a general ontology of configuration. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 1998, 12(4): 357-372
[58] Soininen T. An approach to knowledge representation and reasoning for product configuration tasks: [dissertation]. Finland: Helsinki University of Technology, 2000, 1-24
[59] Soininen T Niemela, Tiihonen J, Sulonen R. Representing configuration knowledge with weight constraint rules. In: Proc of the 2001 AAAI Symposium, 2001, 195-201
[60] Felfernig A, Friedrich G, Jannach D. Conceptual modeling for configuration of mass-customizable products. Artificial Intelligence in Engineering, 2001, 15(2): 165-176
[61] Felfernig A, Friedrich G, Jannach D, Zanker M. Rapid Knowledge Base Development for Product Configuration Systems using the Unified Modeling Language. Taylor and Francis, 2002, 119-138
[62] Felfernig A. Standardized Configuration Knowledge Representations as Technological Foundation for Mass Customization. IEEE Transactions on Engineering Management. 2007, 54(1): 41-56
[63]张劲松,王启富,万立,钟毅方.基于本体的产品配置建模研究.计算机集成制造系统-CIMS, 2003, 9(5): 344-350
[64]张劲松,王启付,刘清华,万立,钟毅方.基于模型的产品智能化配置研究.机械工程学报, 2003, 39(6): 128-134
[65]张劲松,薛春方,刘清华,钟毅方.面向开发链的产品智能化配置技术.中南民族大学学报(自然科学版), 2005, 24(3): 93-96
[66]吴健,陈刚,尹建伟,董金祥.基于本体的产品配置知识共享.浙江大学学报(工学版), 2004, 38(4): 478-484
[67]赵燕伟,胡坚,张国贤.基于OWL本体建模的概念产品配置.中国机械工程, 2004, 15(19): 1725-1728
[68]杨晗,尹建伟,董金祥,罗尚虎.端口-连接型产品配置知识的Java表达.计算机辅助设计与图形学学报, 2005, 17(3): 511-516
[69]尹建伟,杨晗,董金祥,罗尚虎.端口-连接型产品配置本体建立与表达.计算机集成制造系统, 2005, 11(7): 1025-1050
[70] Vei-Chung Liang, Christiaan J, Paredis J. A port ontology for conceptual design of systems. Journal of Computing and Information Science in Engineering, 2004, 4(3): 206-217
[71] Sabin D, Weigel R. Product configuration frameworks-A survey. IEEE intelligent systems, 1998, 14(3): 42-49
[72] Sabin D, Freuder E C. Configuration as composite constraint satisfaction. In: Proc of AAAI, 1996, 28-36
[73] Faltings B, Weigel R. Constraint-based knowledge representation for configuration systems. Technical report No.TR-94/59, Department D’Informatique, 1994, 1-20
[74] Eugene C Freuder, Barry O’Sullivan. Generating tradeoffs for interactive constraint-based configuration. Principles and Practice of Constraint Programming-CP. 2001, 1611-3349
[75]李伟,张孟青,刘光复.基于约束满意问题的产品配置方法.农业机械学报, 2005, 36(7): 126-130
[76] Mittal S, Falkenhainer B. Dynamic constraint satisfaction problems. In: Proc of 8th AAAI, 1990, 25-32
[77] Soininen T, Gelle E, Niemel? I. A fixpoint definition of dynamic constraint satisfaction. In: Proc of CP, 1999, 419-433
[78]李伟,刘光复.一类基于动态约束满足问题的产品配置方法.机械科学与技术. 2005, 24(4): 427-430
[79] Timo Soininen, Esther Gelle. Dynamic constraint satisfaction in configuration. AAAI workshop on configuration. Florida, 1999, 95-100
[80] Stumptner M, Friedrich G E. Generative Constraint-based Configuration of Large Technical Systems. AI EDAM, 1998, 12(4): 307-320
[81] Stumptner M. An overview of knowledge-based configuration. AI Communication, 1997, 10: 111-125
[82] Stumpertner M, Haselbock A. A generative constraint formalism for configuration problems. Advances in artificial intelligence, In: Proc of Third Congress of the Italian Association for Artificial Intelligence, AIIA-93’, 1993, 302-313
[83] Stumptner M, Friedrich G, Haselbock A. Generative constraint-based configuration of large technical systems. AI EDAM, 1998, 12: 307-320
[84] Felischandel G, Friedrich G, Haselbock A, stumptner M. Configuring largesystems using generative constraint satisfaction. IEEE Intelligence Systems and their applications, 1998, 13(4): 59-68
[85] Jianxin Jiao, Mitchell M Tseng. A methodology of developing product family architecture for mass customization. Journal of Intelligence Manufacturing. 1999, 10(1): 3-20
[86] Jeff C. Having it their way: How to successfully customize your mass product. In: Proc of the 1997 40th international conference and exhibition. Washington DC, 1997, 89-91
[87]祁国宁,顾新建,谭建荣.大批量定制技术及其应用.北京:机械工业出版社, 2003, 10-15
[88]周乐,连海佳,季建华.大规模定制模式产品定制程度分析.系统管理学报, 2007, 16(6): 685-689
[89]邵晓峰,季建华,黄培清.基于Internet的大规模定制的实施条件与运作模式.计算机集成制造系统, 2001, 7(12): 53-56
[90] Piller Frank T. Mass customization: Reflections on the state of the concept. The International Journal of Flexible Manufacturing Systems, 2004, 16: 313-334
[91] Blecker T, Abdelkafi N, Kaluza B, Kreutler G. A framwork for understanding the interdepencies between mass customization and complexity. In: Proc of the 2nd international conference on business economics, Management and Marketing. Greece, 2004, 1-15
[92] Piller Frank T, Moslein K, Stotko C. Does mass customization pay. An Economic Approach to Evaluate Customer Integration, 2004, 15(4): 435-444
[93] Tseng M M, Kjellberg T, Lu S, Lu S. Design in the new e-commerce era. Annals of the CIRP, 2003, 52(2): 509-519
[94] Pine B J, Peppers D, Rogers M. Do you want to keep Your Customers Forever. Harvard Business Review, 1995, 73(2): 103-114
[95] Chamberlin E H. Product heterogeneity and public policy. American Econmic Review, 1950, 40(2): 85-92
[96] Broekhuizen T L J, Alsem K J. Success factors for mass customization: A conceptual model. Journal of Market-Focused Management, 2002, 5(4): 309-330
[97] Franke N, Von Hippel E. Satisfying heterogeneous user needs via innovation tookits: The case of apache security software. American Demographics, 2001, 23(7): 51-55
[98] Franke N, Reisinger H. Remaining within-cluster variance: A meta-analysis of the dark side of cluster anlysis. Working Paper, Vienna University of Economics and business administration, 2003, 1-15
[99] Von Hippel E. Perspective: User toolkits for innovation. Journal of Product Innovation Management, 2001, 18(4): 247-257
[100] Pine B JⅡ, Victor B, Boyntonm A C.Making masss customization work. Harvard Business Review, 1993, 71(5): 108-119
[101] Tseng M, Du X. Design by customers of mass customization products. Annals of the CIRP, 1998, 47: 103-106
[102] Davis S. Future Perfect. Addison-Wesley Publication Company, 1987, 50-89
[103] Franke N, Piller F. Toolkits for User Innovation and Design: An exploration of user interaction and value creation. Journal of Product Innovation Management, 2004, 21(6): 401-415
[104] Pine B JⅡ, Gilmore J H. The four faces of mass customization. Harvard Business Review, 1997, 75(1): 91-101
[105] Lampel J, Minlzberg H. Customizing customization. Sloan Management Review, 1996, 38(1): 21-30
[106] Alford D Sackett, Nelder G P. Mass customization-an automotive perspective. International Journal of Production Economics, 2000, 65: 99-110
[107]邵晓峰,黄培清,季建华.大规模定制生产模式的研究.工业工程与管理, 2001, 2: 13-17
[108]祈国宁,杨青海.大规模定制生产模式综述.中国机械工程, 2004, 15(14): 1240-1245
[109] Sabin M, Freuder E C, Wallace R J. Greater efficiency for conditional constraint satisfaction. In: Proc of CP 2003: Principles and practice of constraint programming, 2003, 649-666
[110] Mouhoub M, Sukpan A. Managing conditional and composite CSPs. In: Proc of Canadian Conference on AI, 2007, 216-227
[111] Sabin Mihaela, Freuder Eugene C. Detecting and resolving inconsistency and redundancy in conditional constraint satisfaction problems. In:Web-publised papers of the CP’98 workshop on constraint problem reformulation, Pisa, 1998, 1-6
[112]刘清华,万立,王启富,陈立平.基于条件约束满意问题的产品配置研究.计算机集成制造系统, 2004, 10(11): 1332-1337
[113] Sabin M. Towards more efficient solution of conditional constraint satisfactionproblems: [dissertation]. University of New Hampshire, 2003
[114] Craenen B G W, Eiben A E, Van Hemert J I. Comparing evolutionary algorithms on binary constraint satisfaction problems. IEEE Transactions on Evolutionary Computation, 2003, 7(5): 424-444
[115] Bodirsky Manuel, Kral Daniel. Locally consistent constraint satisfaction problems with binary constraints. Lecture Notes in Computer Science, 2005, 3787: 295-306
[116]杨轻云,孙吉贵,张居阳.最大度二元约束满足问题粒子群算法.计算机研究与发展, 2006, 43(3): 436-441
[117] Aldanonda Michel, Hadi-Hamou khaled, Moynard Guillaume, Lamothe Jacques. Mass customization and configuration: Requirement analysis and constraint based modeling propositions.Integrated Computer-Aided Engineering, 2003, 10(2): 177-189
[118] Lal A. Neighborhood interchangeability for non-binary CSPs & application to databases: [dissertation]. Lincoln: University of Nebraska, 2005
[119] Bacchus Fahiem, Chen Xingquang, Van Beek Peter, Walsh Toby. Binary vs. non-binary constraints. Artificial Intelligence, 2002, 140(1-2): 1-37
[120] Samaras Nikolaos, Sterqiou Kostas. Binary encodings of non-binary constraint satisfaction problems: Algorithms and experimental results. Journal of Artificial Intelligence Research, 2005, 24(7): 641-684
[121] Bessiere C, Reqin J C. MAC and combined heuristics: Two reasons to forsake FC (and CBJ?) on hard problems. In: Proc of Principles and Practice of Constraint Programming - CP96, 1996, 61-75
[122] Bessiere C, Meseguer P, Freuder E C, Larrosa J. On forward checking for non-binary constraint satisfaction. Aritficial Intelligence, 2002, 141(1-2): 205-224
[123] Zhe Liu. Algorithms for constraint satisfaction problems(CSPs): [thesis]. Canada: University of Waterloo, 1998
[124]施伯乐,丁宝康,汪卫.数据库系统教程(第2版).北京:高等教育出版社, 2005, 70-130
[125] Esther Gelle. Solving mixed and conditional constraint satisfaction problems. Constraints, 2003, 8(2): 107-141
[126] Mittal S, Frayman F. Making partial choices in constraint reasoning problems. In: Proc of AAAI, 1987, 631-636
[127] Thomas V, Gaborit P, Aldanondo M. A specificity of CSP in design:Controlling the relevance of the variables in the problem. In: Proc of the Eleventh International Conference on Principles and Practice of Constraint Programming, 2005, 34-41
[128] Mouhoub M, Sukpan A. Managing conditional and composite CSPs. In: Proc of Canadian Conference on AI, 2007, 216-227
[129] Mouhoub M, Sukpan A. Solving conditional and composite constraint satisfaction Problems. In: Proc of the 2007 ACM Symposium on Applied Computing, 2007, 336-337