基于特征函数的产品造型进化设计研究
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摘要
设计创新是企业面对激烈市场竞争的最主要策略之一,创新设计方法要为设计师提供广阔的思路,轻松的设计环境,同时,由于创新多发生于概念设计阶段,创新的数据资源也要保证后续设计的重用。针对创新设计的这些要求,本研究探讨了基于特征函数的产品造型进化设计方法。
在逆向设计、实例设计等设计思想的启发下,借助于进化机制不依赖于环境知识和逻辑思维的特点,建立了以基因组、种群、适应函数和进化操作为基础的进化设计方法。相对于其他创新设计方法,本进化设计在激发设计师的形象思维和灵感思维进而开拓设计思路方面发挥了较大作用;能够实现设计自动化,减轻设计负担;用CAD底层几何API(Application Program Interface)表达的产品造型表象特征数据可以在详细设计阶段得到复用。
在充分了解现代设计的技术手段、设计对象及任务、设计活动和思维的背景下,本文围绕产品造型创新设计展开了进化设计方法的研究,主要完成了如下工作。
(1)首先探讨了产品结构模型、功能模型、产品基因组、种群、适应函数、方案评价、进化操作等设计、进化设计领域的概念、方法,指出基因组实际上就是产品模型,主要是产品的表象结构;种群是相似产品实例的集合,是一种蕴含设计逻辑规律的知识库;适应函数是设计方案评价机制的量化模型;进化操作是进化智能设计推理机制的具体体现;这4个方面构成了进化智能设计模型的结构体系。
然后,从这4个层面上分别研究和总结了现代设计、智能设计以及进化设计近年的国内外发展状况。
(2)在产品结构模型和功能模型的基础上,提出了包含结构和功能信息的、用API函数编码表示产品造型表象特征的基因组模型,CAD底层的几何体API函数及其拓扑API函数被用来表示基因组的结构基因和协调基因,这样的基因粒度利于进化方案的多样性,而且又不失几何和工程语义。
多个功能行为组成了功能模型,功能行为用功能表面表示,将结构基因的功能信息存放在属性表里,用于适应度的计算。基因组是结构基因和拓扑基因构成的符号串,根据它们生成次序和空间拓扑关系可排列为有序串,结构基因按照其在基因组的地位和在造型中的作用主要分为主基因和次基因。这样的基因组是一种树形结构,主基因为每个分支的根结点,拓扑基因为子结点,次基因为孙子结点,这样可转化为二叉树形式,以方便对基因及其功能信息的遍历和基因组相似性计算。
(3)种群库是进化设计创新的源泉,提出了根据相似基因组建立种群库的方法。基因组相似性存在两个方面的含义:相同基因块的数量、所有等同基因相似度的平均值。将多数基因组上排列相同的一系列基因符号串定义为基因块,基因块对应于产品结构的形状特征,防止基因块的分裂可以保持该产品的特色,基因块的甄别采用的是串模式匹配算法。
相似度计算的主要工作是参照目标基因组得到一群个体的相似度,根据相似度值的大小分为不同的种群类,这属于基于内容的三维模型检索技术,与其他检索技术不同,主要通过基因符号串的等同比较和匹配来取得相似个体。
种群库是C/S体系结构,可为进化设计模块提供最优良的个体空间。
(4)为了与进化设计的自动性、高速性和方案的多样性相适应,提出了三层次的适应函数用于进化过程中创新方案的评价。第一层为限定类指标,只有满足基本约束条件的造型才能得到高适应度值,这些限制条件主要是重量和尺寸等。第二层是功能类指标,要设计的产品有一些基本的功能必须满足,将这些基本功能以功能表面的方式组成基准功能模型作为参照物,待评价的造型基因组与它比较,以它们的配对功能表面参数向量作为RBF神经网络的输入,适应度为输出。第三层是适宜类指标,由人工评价得到分值,经综合平均得到适应度,这是一种广泛分布、评价人员众多的评价体系,能与高速的进化设计步调合拍。三类适应度之和是基因组用于选择操作的最终适应度。
(5)为了满足大规模创新设计要求,采用多子群免疫进化机制,将初始种群划分为多个子群,每个子群独立运算若干代后,再合并为一个种群进行运算,最后选择出相对最优的设计方案。进化操作中运用了三个操作算子:免疫选择算子、基因块覆盖交叉算子、基因参数变异算子。
建立在ACIS环境下的进化创新平台采用了并行计算模式,为了协调各个运行端的工作,采用了ACIS-HOOPS的通信和消息机制。以某工艺品企业的茶壶类产品进行了从基因组生成、相似度计算、基准功能模型和适应函数建立到最后的进化操作创新等各个进化过程的计算机模拟,验证了基于特征函数、面向造型的进化创新设计方法的有效性,以及创新平台的可行性。
总之,本研究在产品造型进化设计的基因组、种群、适应函数、进化操作算子4个方面提出了一些较新的概念和模型,为概念设计阶段的产品造型创新提供了进化设计这一方法和过程模型。这种进化设计模型对于汽车零部件、家居用品、工艺品等产品的结构和外观造型的创新有着较大的实用价值。
Creative design is one of the most important ploys which enterprises can choose faced on the intense competition in the market. The creative design method can provide for designers a broader line of thougnt, relaxed design environment, moreover, the design data which it often produces in the stage of concept design should be reused in the follow-up design phases. In response to these requests of the creative design method, the product model evolutionary design based on feature functions was proposed.
The evolutionary design system based on genome, population, fitness function, evolutionary operation was established by the thoughts of backward design, case-based design, etc., and with the traits that the evolutionary mechanism does not rely on environment knowledge and logic thinking. It can stimulate designers’image thinking and inspiration thinking to widen their creative thoughts, and it can reduce design burden by automatically completing the design process, in addition, the model image features based on the geometry API (Application Program Interface) in CAD can be reused in the detail design stage.
After introducing the background, objects and tasks, activities and thoughts of modern design technology, the product model-oriented evolutionary design method was researched.
1) The concepts and methods such as product structure, product function, product genome, population, fitness function, plans evaluation, evolutionary operation, etc. were firstly discussed. In fact, the genome as another form of product model is composed of image components; the population is a set of similar product instances and a knowledge repository containing design logic laws; the fitness function is a kind of quantitative model of design plans evaluation; the evolutionary operation is a concrete reasoning mechanism which the evolutionary design adopted. Then the recent research development on the four aspects of modern design, intilligent design, evolutionary design were summarized.
2) The product genome expressed by API as product model image feature function codes including the information of structure and function was proposed at the basis of product structure modelling and function modelling. The geometry API and topology API were respectively defined as construction genes and coordination or topology genes in the genome, so the gene granularity is beneficial to the diversity of evolutionary design plans, and furthermore is not losing geometry and engineering semantics.
The product function is modelling by functional behavior. The construction genes’functional behavior expressed by functional surfaces and placed in their attribute table, is used for fitness calculation. The genome is a symbol string of construction genes and topology genes, which is ranked according to the generated sequences and spatial topological relations. The construction genes are classified into primary genes and secondary genes in the light of their roles in the product modelling. The genome is a kind of tree structure, in which the primary genes are the root nodes of each branch, the topology genes are son nodes, and the secondary genes are grandson nodes, therefore, the genome can be converted into a binary tree structure which is easier to ergodicity of genes and their function information or similarity calculation.
3) The population is the source of evolutionary creative design, the method building up the population with similar individual genomes was proposed. The similarity between two genomes is related with the number of the equal gene blocks and the average similarity of the equal genes. The gene block corresponding with the shape features, which is a sequence of gene codes with the same sort, can display the product characteristics under no-split condition, which was picked out by the string pattern matching algorithm.
By comparing with the target genome, the individual similarity is obtained, on which the different genome groups are divided. It is the content-based 3D model search technology by comparing and matching symbol strings to get the similar genome, which is different from other search technology.
The population database as a C/S structure can provide the best individual space for the evolutionary design module.
4) The 3-level fitness function is used to evaluate the creative plans in the process of evolutionary design, which fits into automatic, high-speed, diversity evolutionary design. The limit indexes at the first level such as weight and dimension are the basic constraint conditions. The basic functional indexes at the second level the new qualified genomes must possess are some functional surfaces which form the benchmark function model as the reference. The parameter vectors on matching functional surfaces of the genome to be evaluated by comparing with the benchmark function model are input into the RBF neural network and then the genome fitness is output. The subjective indexes at the third level are scored by human, their average scores is the fitness. The third level is a widely distributed, large evaluating system to keep pace with the high-speed evolutionary design. The sum of the three classes of fitness is the fitness of the evaluated genome for selection operation.
5) The multi-subgroup immune evolutionary mechanism is adopted to meet a large-scale creative design. The initial population is at first divided into several subgroups, the evolutionary design will have been running independently in every subgroup for some generations, and then the excellent individuals from these subgroups are regrouped to continue their evolution until some relatively optimal plans emerge. The three operators which are immune selection, crossover covered by gene block, mutation of parameter in genes, are introduced in the evolutionary design.
The evolutionary creative design platform in the ACIS-HOOPS environment adopts parallel computing and message-passing paradigm to conform all modules. The evolutionary test of some teapot models demonstrated the effectiveness and feasibility of the model-oriented evolutionary creative design process from genome formation, similarity calculation, benchmark function model and fitness function to evolutionary operations.
To sum up, some novel concepts and methods from the perspective of genome, population, fitness function, evolutionary operators in the product model-oriented evolutionary design have been studied, and a kind of evolutionary design thinking and design process model have been put forward for the product model innovation in the concept design stage. The evolutionary design method has the great practical value to the creative design of product structures and models in the field of auto parts, home appliances and supplies, crafts, and so on.
在逆向设计、实例设计等设计思想的启发下,借助于进化机制不依赖于环境知识和逻辑思维的特点,建立了以基因组、种群、适应函数和进化操作为基础的进化设计方法。相对于其他创新设计方法,本进化设计在激发设计师的形象思维和灵感思维进而开拓设计思路方面发挥了较大作用;能够实现设计自动化,减轻设计负担;用CAD底层几何API(Application Program Interface)表达的产品造型表象特征数据可以在详细设计阶段得到复用。
在充分了解现代设计的技术手段、设计对象及任务、设计活动和思维的背景下,本文围绕产品造型创新设计展开了进化设计方法的研究,主要完成了如下工作。
(1)首先探讨了产品结构模型、功能模型、产品基因组、种群、适应函数、方案评价、进化操作等设计、进化设计领域的概念、方法,指出基因组实际上就是产品模型,主要是产品的表象结构;种群是相似产品实例的集合,是一种蕴含设计逻辑规律的知识库;适应函数是设计方案评价机制的量化模型;进化操作是进化智能设计推理机制的具体体现;这4个方面构成了进化智能设计模型的结构体系。
然后,从这4个层面上分别研究和总结了现代设计、智能设计以及进化设计近年的国内外发展状况。
(2)在产品结构模型和功能模型的基础上,提出了包含结构和功能信息的、用API函数编码表示产品造型表象特征的基因组模型,CAD底层的几何体API函数及其拓扑API函数被用来表示基因组的结构基因和协调基因,这样的基因粒度利于进化方案的多样性,而且又不失几何和工程语义。
多个功能行为组成了功能模型,功能行为用功能表面表示,将结构基因的功能信息存放在属性表里,用于适应度的计算。基因组是结构基因和拓扑基因构成的符号串,根据它们生成次序和空间拓扑关系可排列为有序串,结构基因按照其在基因组的地位和在造型中的作用主要分为主基因和次基因。这样的基因组是一种树形结构,主基因为每个分支的根结点,拓扑基因为子结点,次基因为孙子结点,这样可转化为二叉树形式,以方便对基因及其功能信息的遍历和基因组相似性计算。
(3)种群库是进化设计创新的源泉,提出了根据相似基因组建立种群库的方法。基因组相似性存在两个方面的含义:相同基因块的数量、所有等同基因相似度的平均值。将多数基因组上排列相同的一系列基因符号串定义为基因块,基因块对应于产品结构的形状特征,防止基因块的分裂可以保持该产品的特色,基因块的甄别采用的是串模式匹配算法。
相似度计算的主要工作是参照目标基因组得到一群个体的相似度,根据相似度值的大小分为不同的种群类,这属于基于内容的三维模型检索技术,与其他检索技术不同,主要通过基因符号串的等同比较和匹配来取得相似个体。
种群库是C/S体系结构,可为进化设计模块提供最优良的个体空间。
(4)为了与进化设计的自动性、高速性和方案的多样性相适应,提出了三层次的适应函数用于进化过程中创新方案的评价。第一层为限定类指标,只有满足基本约束条件的造型才能得到高适应度值,这些限制条件主要是重量和尺寸等。第二层是功能类指标,要设计的产品有一些基本的功能必须满足,将这些基本功能以功能表面的方式组成基准功能模型作为参照物,待评价的造型基因组与它比较,以它们的配对功能表面参数向量作为RBF神经网络的输入,适应度为输出。第三层是适宜类指标,由人工评价得到分值,经综合平均得到适应度,这是一种广泛分布、评价人员众多的评价体系,能与高速的进化设计步调合拍。三类适应度之和是基因组用于选择操作的最终适应度。
(5)为了满足大规模创新设计要求,采用多子群免疫进化机制,将初始种群划分为多个子群,每个子群独立运算若干代后,再合并为一个种群进行运算,最后选择出相对最优的设计方案。进化操作中运用了三个操作算子:免疫选择算子、基因块覆盖交叉算子、基因参数变异算子。
建立在ACIS环境下的进化创新平台采用了并行计算模式,为了协调各个运行端的工作,采用了ACIS-HOOPS的通信和消息机制。以某工艺品企业的茶壶类产品进行了从基因组生成、相似度计算、基准功能模型和适应函数建立到最后的进化操作创新等各个进化过程的计算机模拟,验证了基于特征函数、面向造型的进化创新设计方法的有效性,以及创新平台的可行性。
总之,本研究在产品造型进化设计的基因组、种群、适应函数、进化操作算子4个方面提出了一些较新的概念和模型,为概念设计阶段的产品造型创新提供了进化设计这一方法和过程模型。这种进化设计模型对于汽车零部件、家居用品、工艺品等产品的结构和外观造型的创新有着较大的实用价值。
Creative design is one of the most important ploys which enterprises can choose faced on the intense competition in the market. The creative design method can provide for designers a broader line of thougnt, relaxed design environment, moreover, the design data which it often produces in the stage of concept design should be reused in the follow-up design phases. In response to these requests of the creative design method, the product model evolutionary design based on feature functions was proposed.
The evolutionary design system based on genome, population, fitness function, evolutionary operation was established by the thoughts of backward design, case-based design, etc., and with the traits that the evolutionary mechanism does not rely on environment knowledge and logic thinking. It can stimulate designers’image thinking and inspiration thinking to widen their creative thoughts, and it can reduce design burden by automatically completing the design process, in addition, the model image features based on the geometry API (Application Program Interface) in CAD can be reused in the detail design stage.
After introducing the background, objects and tasks, activities and thoughts of modern design technology, the product model-oriented evolutionary design method was researched.
1) The concepts and methods such as product structure, product function, product genome, population, fitness function, plans evaluation, evolutionary operation, etc. were firstly discussed. In fact, the genome as another form of product model is composed of image components; the population is a set of similar product instances and a knowledge repository containing design logic laws; the fitness function is a kind of quantitative model of design plans evaluation; the evolutionary operation is a concrete reasoning mechanism which the evolutionary design adopted. Then the recent research development on the four aspects of modern design, intilligent design, evolutionary design were summarized.
2) The product genome expressed by API as product model image feature function codes including the information of structure and function was proposed at the basis of product structure modelling and function modelling. The geometry API and topology API were respectively defined as construction genes and coordination or topology genes in the genome, so the gene granularity is beneficial to the diversity of evolutionary design plans, and furthermore is not losing geometry and engineering semantics.
The product function is modelling by functional behavior. The construction genes’functional behavior expressed by functional surfaces and placed in their attribute table, is used for fitness calculation. The genome is a symbol string of construction genes and topology genes, which is ranked according to the generated sequences and spatial topological relations. The construction genes are classified into primary genes and secondary genes in the light of their roles in the product modelling. The genome is a kind of tree structure, in which the primary genes are the root nodes of each branch, the topology genes are son nodes, and the secondary genes are grandson nodes, therefore, the genome can be converted into a binary tree structure which is easier to ergodicity of genes and their function information or similarity calculation.
3) The population is the source of evolutionary creative design, the method building up the population with similar individual genomes was proposed. The similarity between two genomes is related with the number of the equal gene blocks and the average similarity of the equal genes. The gene block corresponding with the shape features, which is a sequence of gene codes with the same sort, can display the product characteristics under no-split condition, which was picked out by the string pattern matching algorithm.
By comparing with the target genome, the individual similarity is obtained, on which the different genome groups are divided. It is the content-based 3D model search technology by comparing and matching symbol strings to get the similar genome, which is different from other search technology.
The population database as a C/S structure can provide the best individual space for the evolutionary design module.
4) The 3-level fitness function is used to evaluate the creative plans in the process of evolutionary design, which fits into automatic, high-speed, diversity evolutionary design. The limit indexes at the first level such as weight and dimension are the basic constraint conditions. The basic functional indexes at the second level the new qualified genomes must possess are some functional surfaces which form the benchmark function model as the reference. The parameter vectors on matching functional surfaces of the genome to be evaluated by comparing with the benchmark function model are input into the RBF neural network and then the genome fitness is output. The subjective indexes at the third level are scored by human, their average scores is the fitness. The third level is a widely distributed, large evaluating system to keep pace with the high-speed evolutionary design. The sum of the three classes of fitness is the fitness of the evaluated genome for selection operation.
5) The multi-subgroup immune evolutionary mechanism is adopted to meet a large-scale creative design. The initial population is at first divided into several subgroups, the evolutionary design will have been running independently in every subgroup for some generations, and then the excellent individuals from these subgroups are regrouped to continue their evolution until some relatively optimal plans emerge. The three operators which are immune selection, crossover covered by gene block, mutation of parameter in genes, are introduced in the evolutionary design.
The evolutionary creative design platform in the ACIS-HOOPS environment adopts parallel computing and message-passing paradigm to conform all modules. The evolutionary test of some teapot models demonstrated the effectiveness and feasibility of the model-oriented evolutionary creative design process from genome formation, similarity calculation, benchmark function model and fitness function to evolutionary operations.
To sum up, some novel concepts and methods from the perspective of genome, population, fitness function, evolutionary operators in the product model-oriented evolutionary design have been studied, and a kind of evolutionary design thinking and design process model have been put forward for the product model innovation in the concept design stage. The evolutionary design method has the great practical value to the creative design of product structures and models in the field of auto parts, home appliances and supplies, crafts, and so on.
引文
[1]中国社会科学院语言研究所词典编辑室编.现代汉语词典[M].商务印书馆, 2005.
[2]刘美华.产品设计原理[M].北京:北京大学出版社,2008: 1-20.
[3]王启广,叶平.现代设计理论[M].徐州:中国矿业大学出版社, 2005:1-10.
[4]王受之.世界现代设计史[M].北京:中国青年出版社,2002,1-17.
[5]梅格斯著,柴常佩译.二十世纪视觉传达设计史[M].武汉:湖北美术出版社,1994:2-13.
[6]奚传绩.设计艺术经典论著选读[M].南京:东南大学出版社,2002:1-25.
[7]安毓英.产品装潢设计百略[M].北京:中国轻工业出版社,1995:5-19.
[8] Gero J S, Neill T M. An approach to the analysis of design protocols[J]. Design Studies, 1998, 19(1): 21-61.
[9]潘云鹤.形状设计思维过程模式[J].浙江大学学报:自然科学版, 1993, 27(3).
[10] Gero J S, Kannengiesser U. Function-behaviour-structure: A model for social situated agents [EB/OL]. http://cs.gmu.edu/~jgero//publications/2003.
[11] Gero J S. Computational models of innovative and creative design processes[J]. Technological Forecasting and Social Change, 2000, 64: 183-196.
[12]唐林.产品概念设计基本原理和方法[M].国防工业出版社,2006.
[13]张建明,魏小鹏,张德珍.产品概念设计的研究现状及其发展方向[J].计算机集成制造系统, 2003, 9(08):613-620.
[14] Pahl G, Beitz W. Engineering design: a systematic approach [M]. Springer Verlag, 1996.
[15]孙守迁,包恩伟,陈蘅,潘云鹤.计算机辅助概念设计研究现状和发展趋势[J].中国机械工程,1999, 03: 105-109.
[16]陈亚华.基于快速设计策略的产品概念设计理论及方法研究[D].重庆大学, 2002.
[17]赵文辉,李思昆.电子产品并行设计方法及虚拟原型仿真环境研究[D].长沙:国防科技大学, 2002.
[18]刘雄飞,王逢瑚.基于网络的交互式虚拟室内环境的研究与实现[D].东北林业大学, 2006.
[19]霍志濮,黄克正.机电系统虚实一体化的创新设计自动化理论与技术研究[D].山东大学,2007.
[20]徐延宁,孟祥旭.虚拟样机建模技术与协同装配方法研究[D].山东大学,2006.
[21]郭万林.机械产品全生命周期设计[J].中国机械工程, 2002, 13(13):1153-1158.
[22]徐志刚,刘维民.设计自动化的深刻内涵与广义外延[J].机械设计, 2002, 6(19).
[23]王艳东,黄克正.以人为原型的设计自动化理论和技术研究[D].山东大学,2006.
[24]高常青,黄克正,张勇.基于能量转换的机械产品概念设计自动化研究与实现[J].中国机械工程, 2007, 18(06).
[25]徐志刚,周以齐,刘庆亮,艾兴.产品结构创新设计自动化理论及CAD系统构造[J].中国机械工程, 2001, 12(08).
[26]龚勉,赵波.超变量几何相关性技术WAVE及应用[J].机械设计, 2004, 21(12).
[27]曹春红,李文辉.几何约束求解技术的研究[D].吉林大学, 2005.
[28] Fang Weidong, Tang Ming Xi, Frazer J H. Constructing an intelligent collaborative design environment with distributed agents[C]. Computer Supported Cooperative Work in Design, The 8th International Conference on 26-28 May 2004, 1: 329 - 335.
[29]王安麟,姜涛,刘广军.智能设计[M].北京:高等教育出版社,2008:1-36.
[30] Hoile C, Tateson R. Design by morphogenesis[J]. BT Technology Journal, 2000, 18(4) : 112-121.
[31] Beurier G, Michel F, Ferber J. A morphogenesis model for multiagent embryogeny[C]. The Tenth International Conference on the Simulation and Synthesis of Living Systems, Cambridge, MA, 2006: 84-90.
[32] Kumar S, Bentley P J. The ABCs of evolutionary design: investigating the evolvability of embryogenies for morphogenesis[C].In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-1999, Morgan Kaufmann Publishers, July 1999: 164-170.
[33] Kumar S. Implicit evolvability: an investigation into the evolvability of an embryogeny[C]. 14 Evolutionary Computation Conference (GECCO 2000), July 8-12, 2000, Las Vegas.
[34] Bentley P J, Wakefield J P. Overview of a generic evolutionary design system[C].In Proceedings of the 2nd On-line Workshop on Evolutionary Computation (WEC2), 1996, Nagoya University, Japan.
[35] Parmee I C. Evolutionary and adaptive strategies for engineering design - an overall framework[C]. Evolutionary Computation, IEEE International Conference on 13-16 Apr. 1997: 373– 378.
[36] Bentley P J, Jonathan P W. The table: an illustration of evolutionary design using genetic algorithms[C]. Genetic Algorithms in Engineering Systems: Innovations and Applications, First International Conference on 12-14 Sep. 1995: 412-418.
[37] Bentley P J, Jonathan P. W. Conceptual evolutionary design by a genetic algorithm[J]. Engineering Design Automation, 1997, 3(2): 119-131.
[38]谭建荣冯毅雄.设计知识建模、演化与应用[M].北京:国防工业出版社,2007: 1-30.
[39] Gero J S. Situated design computing: principles[M]. Topping B H V. (Editor). Civil Engineering Computations: Tools and Techniques, Saxe-Coburg Publications, 2007: 123-132.
[40] Gero J S. Computational models of creative designing based on situated cognition [C]. Proceedings of the 4th conference on Creativity & cognition, Loughborough, UK, 13-16/10/2002: 3-10.
[41] Kan J W, Gero J S. Acquiring information from linkography in protocol studies of designing[C]. International Conference on Engineering Design, ICED’07, 28–31/8/2007, Paris, France.
[42] Bilda Z, Gero J S. Does sketching off-load visuo-Spatial working memory[M]. Studying Designers'05, Key Centre of Design Comp & Cogntn, 2005.
[43] Kan J W. Using the FBS ontology to capture semantic design information in design protocol studies[C]. DTRS7: Design Meeting Protocols, 19-21/9/2007, London, UK.
[44] Sosa R, Gero J S. A computational study of creativity in design: the role of society[J]. AI EDAM: Artificial Intelligence for Engineering Design, Analysis, and Manufactoring, 2005, 19(4): 229-244.
[45] Bentley P J, Sanjeev K. Three ways to grow designs: A comparison of embryogenies for an evolutionary design problem[C]. Genetic and Evolutionary Computation Conference (GECCO'99), Morgan Kaufmann Publishers, Orlando, Florida, USA: 35-43.
[46] Tina Yu, Bentley P J. Methods to evolve legal phenotypes[C].Proceedings of the Fifth Int. Conf. on Parallel Problem Solving From Nature, Amsterdam, 27-30 Sept, 1998: 280-291.
[47] Meng Q C, Feng T J, Zhou C J, Bo J H. Genetic algorithms encoding study and a sufficient convergence condition of Gas [C].Systems, Man and Cybernetics, IEEE International Conference on 10/12/-10/15/1999, Tokyo, Japan, 1: 649-652.
[48]周开俊,李东波,童一飞.面向产品创新设计的功能模块划分方法[J].计算机辅助设计与图形学学报, 2007, 19(1): 73-83.
[49]邓益民,郑堤.机电产品功能与行为表达方法综述[J].工程设计学报, 2008, 3.
[50] Robert J.S.著,杨炳钧,陈燕,邹枝玲,译.认知心理学[M].北京:中国轻工业出版社,2006:83-110.
[51] Gero, J S. Design prototypes: a knowledge representation schema for design[J]. AI Magazine, 1990, 11(4): 26-36.
[52]彭颖红,胡洁. KBE及其在产品设计中的应用[M].上海:上海交通大学出版社,2007: 94-140.
[53]张三元,孙守迁,潘云鹤.基于产品反求工程的产品创新设计方法[J].计算机辅助设计与图形学学报, 2000, 11.
[54]张建明,魏小鹏,张德珍.产品概念设计的研究现状及其发展方向[J].计算机集成制造系统, 2003, 9(08):2-9.
[55]徐宗本,张讲社,郑亚林.计算智能中的仿生学:理论与算法[M].北京:科学出版社,2007:107-160.
[56] Simon H. Neural networks: A comprehensive foundation (Second Edition) [M]. Prentice Hall, 1999.
[57] Ham F M, Kostanie I. Priciples of neuro computing for science & engineering [M]. McGraw Hill, 2001.
[58]张德丰. MATLAB神经网络应用设计[M].北京:机械工业出版社,2009: 157-179.
[59]赵涛.管理学常用方法[M].天津:天津大学出版社,2006:314-327.
[60]李春葆.数据结构教程[M].北京:清华大学出版社,2006,131-166.
[61]景振毅,张泽兵,董霖. MATLAB 7.0实用宝典[M].北京:中国铁道出版社,2009:53-78.
[62]刘弘.支持产品创新的协同设计系统研究技术报告[R].济南:山东师范大学,2006.
[63] Gero J S. AI EDAM at 2000: artificial intelligence in designing[J]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2007, 21: 17–18.
[64]周济.机械设计专家系统概论[M].武汉:华中理工大学出版社,1989.
[65]蔡自兴.人工智能及其应用[M].北京:清华大学出版社, 2005.
[66]张丽平,胡上序.粒子群优化算法的理论和实践[D].浙江大学, 2005.
[67]高隽.智能信息处理方法导论[M].北京:机械工业出版社, 2004.
[68]邢文训,谢金星.现代优化计算方法[M].北京:清华大学出版社, 2005.
[69]危辉,潘云鹤.从知识表示到表示:人工智能认识论上的进步[J].计算机研究与发展, 2000, 37(7):819-825.
[70]苏宝华.面向大量定制生成的产品建模理论、方法及其应用研究[D].杭州:浙江大学,1998.
[71] John M U. A STEP-based object-oriented product model for process planning[J]. Computers ind. Engng., 1996, 31(1/2): 185-188.
[72] Ping Yi Chao, Shen Chout Yeh. Representation of standard mechanical components in a STEP-based product data management system[J]. International Journal of Computer Applications in Technology, 1999, 12(1): 16-26.
[73]何小朝,沈梅,张铁昌.并行CAD/CAM集成中的产品模型表示方法研究[J].航空学报,2000,21(1): 43-47.
[74]王琪,刘永贤,刘彪.协同设计环境下的产品造型技术[J].制造技术与机床, 2006, 9.
[75]欧松,周其节. CIMS环境下的产品设计自动化研究[D].华南理工大学, 1997.
[76] Peak R S, Fulton R E, Nishigaki I, Okamoto N. Integrating engineering design and analysis using a multi-representation approach[J]. Engineering with Computers, 1998, 14(2): 93-114.
[77] Lee J Y. Shape representation and interoperability for virtual prototyping in a distributed design environment[J]. International journal of advanced manufacturing technology, ISSN 0268-3768, 2001, 17(6): 425-434.
[78]唐文献,方明伦. KBE环境下面向协同创新的产品开发支持系统研究[D].上海大学,2003.
[79]陈磊,叶修梓.异构CAD产品模型的数据分层表示及重用技术研究[D].浙江大学, 2008.
[80] Horvath L, Rudas I J. Evaluation of Petri net process model representation as a tool of virtual manufacturing[C]. Systems, Man and Cybernetics, IEEE International Conference on 11-14 Oct 1998, 1: 178 - 183.
[81] Case K, Harun W A W. Feature-based representation for manufacturing planning[J]. International Journal of Production Research, 2000, 38(17): 4285-4300.
[82] Tallinen T, Osuna R V, Lastra J L M, Tuokko R. Product model representation concept for the purpose of assembly process modeling[C]. Assembly and Task Planning, the IEEE International Symposium on 10-11 July 2003: 222–227.
[83] Jabbour T, Mascle C, Maranzana R. A database for the representation of assembly features in mechanical products[J]. International Journal of Computational Geometry and Apllications, 1998, 8(5): 483-509.
[84]刘晓冰,袁长峰,邢英杰,王万雷.基于类和特征的产品配置建模[J].计算机集成制造系统, 2005, 11(8): 1057-1063.
[85]谢清,谭建荣,冯毅雄.面向配置设计的产品功构建模方法[J].计算机辅助设计与图形学学报, 2006, 18(4): 574-579.
[86] Pierre D L. An assembly-oriented product family representation for integrated design[J]. IEEE transactions on robotics and automation, ISSN 1042-296X , 2003, 19(1): 75-88.
[87] Kusiak A, Chun-Che Huang. Development of modular products[J]. Components, Packaging and Manufacturing Technology, Part A, IEEE Transactions on Dec 1996, 19(4): 523–538.
[88]姜大志,孙俊兰.成组技术在产品快速设计系统中的应用[J].机械设计, 2005, 22(8): 57-59.
[89]王启富杨磊黄运保王波兴.协同产品开发中的产品模型轻量化技术[J].计算机辅助设计与图形学学报, 2006, 18(01):108-113.
[90] Mehalawi R, Allen M. A database system of mechanical components based on geometric and topological similarity, Part I: representation[J]. Computer-Aided Design, 2003, 35(1): 83-94.
[91]刘云华,刘俊,陈立平.产品三维数据模型轻量化表示实现[J].计算机辅助设计与图形学学报, 2006, 18(04).
[92] Yongmin Zhong, Mueller-Wittig W, Weiyin Ma. A model representation for solid modeling in a virtual reality environment[C]. Shape Modeling International Proceedings, 2002: 183–190.
[93]王靖滨,俞杰,耿卫东,潘云鹤.基于FBS的产品创新设计模型[J].计算机辅助设计与图形学学报, 2000, 12(11): 824-826.
[94]宋慧军,林志航,罗时飞.机械产品概念设计中的知识表示[J].计算机辅助设计与图形学学报, 2003, 15(4): 438-443.
[95]张帅,冯培恩.复合功能产品概念设计建模理论及自动化求解方法研究[D].浙江大学,2005.
[96]付相君,李善平,郭鸣.产品数据模型的本体知识表达[J].计算机辅助设计与图形学学报, 2005, 17(3): 570-577.
[97]邹光明,胡于进,王兴东,孔建益.概念设计产品表示模型研究[J].武汉科技大学学报(自然科学版), 2008, 31(02).
[98]欧阳渺安.面向对象的智能产品建模技术的研究[J].现代制造工程, 2005, 06: 40-42.
[99]张帅,冯培恩,潘双夏,陈泳,朱爱华.基于循环映射模型的概念设计自动化策略研究[J].计算机辅助设计与图形学学报, 2005, 17(3): 491-497.
[100] Buur J. A theoretical approach to mechatronics design [M]. IK Publisher, 1990.
[101] Schmekel H. Functional models and design solutions[J]. Annals of CIRP, 1989, 38:129-132.
[102] Stone R B, Wood K L, Crawford R H. A heuristic method for identifying modules for product architectures[J]. Design Studies, 2000, 21(1): 5-31.
[103]俞杰,耿卫东,潘云鹤.面向产品创新设计的CAD方法综述[J].计算机辅助设计与图形学学报, 1999, (02).
[104]谭同德,童秉枢,王涛.产品结构设计的数据模型[J].计算机辅助设计与图形学学报, 2000, 12(1): 11-16.
[105]李书田,郑联语,汪叔淳.集成环境中基于特征顺序的产品建模方法研究[J].计算机辅助设计与图形学学报,1999, 11(5): 420-425.
[106] Gero J S, Ricardo S. Complexity measures as a basis for mass customization of novel designs[J]. Environment and Planning B: Planning and Design, 2007, 35(1) : 3– 15.
[107] Bentley P J, Jonathan P W. Generic representation of solid-object geometry for genetic search[J]. Microcomputers in Civil Engineering, 1996, 11(3): 153-161.
[108] Tyson R B. Applying the design structure matrix to system decomposition and integration problems: A review and new directions[J]. Engineering Management, IEEE Transactions on Aug. 2001, 48(3): 292-306.
[109]董雁,谭建荣.结构定性建模理论及其在机械产品类比设计中应用研究[D].浙江大学, 2004.
[110]冯力,叶尚辉.支持机械创新设计CAD方法的探索[D] .西安电子科技大学, 1999.
[111]赵婷婷,魏小鹏.基于直觉启发和改进遗传算法的形状概念设计[D].大连理工大学, 2005.
[112] Sasajima M, Kitamura Y. Presentation language for behavior and function[J]. FBRL-Expert Systems with Application, 1996, 10(3/4): 471-479.
[113] Qian L. Function-behavior-structure paths and their role in analogy-based design[J]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing -AI EDAM, 1996, 10(4): 289-312.
[114]张勇,黄克正.基于同步公差设计的概念结构设计优化[D].山东大学, 2006.
[115]顾正朝,高曙明.并行环境下注塑件智能设计支撑技术研究[J].计算机辅助设计与图形学学报, 1999, 11(1): 39-42.
[116]谢清,谭建荣,冯毅雄.面向配置设计的产品功构建模方法[J].计算机辅助设计与图形学学报, 2006, 18(4): 574-579.
[117]谢来勇,郝永平,张秉权.基于XML的产品信息模型表示及应用[J].计算机集成制造系统, 2004, 10(12): 1492-1496.
[118] Xinqin Gao, Zongbin Li. Computer aided conceptual design of mechanical product using polychromatic sets[C]. Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation, 25-28 June, 2006, Luoyang, China: 1168-1174.
[119] Gero J S, Kazakov V. On measuring the visual complexity of 3D solid objects[J]. Journal of Design Sciences and Technology, 2003, 12(1): 35-44.
[120]余军合,吴昭同.面向全生命周期虚拟产品模型的研究与应用[D].浙江大学, 2002.
[121]蔡自兴.人工智能及其应用[M].北京:清华大学出版社, 2005.
[122]蒋占四,李尚平,邓劲莲.甘蔗收割机械智能设计系统的研究开发[J].计算机辅助设计与图形学学报, 2004, 16(12): 1754-1757.
[123] Zhang W Y, Tors B , Britton G, et al. A knowledge-based expert system for functional design of engineering systems[J]. Engineering with Computers , 2001, 17 (4): 339-353.
[124]王玉新.机械系统概念设计自动化方法[J].机械工程学报, 2002, 38(10):148-153 .
[125]王小同范立础.智能设计系统的IDS模型[J].模式识别与人工智能, 1996, 9(2).
[126]郝泳涛.基于特征编码组和人工神经网络的模式化智能工艺设计系统关键技术研究[D].上海:上海交通大学, 1999.
[127]郝泳涛,赵卫东,李启炎.基于模式化知识和人工神经网络的智能设计系统框架研究[J].计算机辅助设计与图形学学报, 2001, 13(9): 834-839.
[128]钟佩思,高国安.基于神经网络块的混合型方案设计知识库系统[J].机械设计, 1999, 16 (5): 1-2.
[129]杨海军,李敏强.进化计算中的模式理论、涌现及应用研究[D].天津大学, 2004.
[130]李建武,李敏强.遗传算法适应值曲面及遗传算法困难度分析[D].天津大学, 2002.
[131] Sekanina L. Evolutionary algorithms[D]. Brno University, 2005.
[132] Thomas B. Evolutionary computation[M]. IOP Publishing Ltd., 1997.
[133]李敏强,寇纪松.遗传算法的基本理论和应用[M].北京:科学出版社, 2004.
[134]徐宗本,张讲社,郑亚林.计算智能中的仿生学:理论与算法[M].北京:科学出版社, 2007.
[135] Schwefel H P, Kursawe F. On natural life’s tricks to survive and evolve[C]. Evolutionary Computation, IEEE World Congress on Computational Intelligence on 4-9 May 1998: 1-8.
[136] Parmee I C, Bonham C R. Towards the support of innovative conceptual design through interactive evolutionary computing strategies[J]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing– AI EDAM, 2000,14(1): 3-16.
[137]冯培恩,陈泳,张帅等.基于产品基因的概念设计[J] .机械工程学报, 2002, 38(10): 1-6.
[138] Bentley P J. Aspects of evolutionary design by computers[M]. Spinger-Verlag London Limited. UK, 1999.
[139] Rodríguez M A, Jarur M C. A genetic algorithm for searching spatial configurations[C]. Evolutionary Computation, IEEE Transactions on 2005, 9 (3): 252- 270.
[140] Koza J R. Automated synthesis of analog electrical circuits by means of genetic programming[C]. Evolutionary Computation, IEEE Transactions on 1997, 1(2): 109–128.
[141]王小港,姚林声.遗传算法在VLSI设计自动化中的应用研究[D].中国科学院, 2001.
[142] Drechsler R. Evolutionary algorithms for VLSI CAD[M]. Kluwer Academic Publishers, 1998.
[143] Lamas A, Pe?a F, Duro R. Automatic evolutionary design of control systems for underwater vehicles[C]. International Conference on Computational Intelligence for Modelling, Control and Automation and Intelligent Agents, Web Technologies and Internet Commerce on 28 Nov. 2006- 1 Dec. 2006: 157-157.
[144] Krzysztof W, Bentley P J. Optimising the performance of a Formula one car using a genetic algorithm[C]. International conference on parallel problem solving from nature, Birmingham, 18/09/2004: 702-711.
[145]舒启林,郝博.机械产品方案设计自动化研究[J].中国机械工程, 2000, 13(19): 1676-1679.
[146] Richard H. D. Engineering design optimization with genetic algorithms[C]. Northcon Conference Proceedings on 10/21-10/23/1998, Seattle, WA, USA: 114-119.
[147] Tetsushi K, Fumitoshi M, Ranajit C. Proposition of twisting mode of locomotion and GA based motion planning for transition of locomotion modes of 3-dimensional snakelike robot[C]. Robotics and Automation, ICRA’02, IEEE International Conference on 2002, 2: 1507-1512.
[148] Miha K. Genetic algorithm approach for autonomous vehicles[C]. Industrial Technology, IEEE International Conference on 10-12 Dec. 2003, 2: 974–978.
[149] Medina L, Díaz E, Rubio E, Rodríguez K. Design of a planar array of sensors for 3D location using genetic algorithms[C]. Ultrasonics, IEEE Symposium on 5-8 Oct. 2003, 2: 1384–1387.
[150]刘弘,刘希玉.支持外观造型创新设计的进化计算方法[J].计算机辅助设计与图形学学报, 2006, 18(1): 101-107.
[151] Jussi Angesleva. Evolutionary computation in creative design[D]. Berlin University, 2005.
[152]冯毅雄,谭建荣,张树有,马辉.集成环境下创新产品进化设计技术研究[J].计算机集成制造系统, 2006, 12(1): 1-20.
[153] Rieffel John. Evolving assembly plans for fully automated design and assembly[C]. Evolvable Hardware, NASA/DoD Conference on 29 June-1 July 2005: 165-170.
[154] Chocron O, Bidaud P. Genetic design of 3D modular manipulators[C].Robotics and Automation, IEEE International Conference on 20-25 Apr. 1997, 1: 223-228.
[155] Bentley P J, Gordon T, Kim J, Kumar S. New trends in evolutionary computation[C]. Proceedings of Congress on Evolutionary Computation (CEC-2001), Seoul, Korea.
[156] Kumar S, Bentley P J. Computational embryology: past, present and future[M]. MIT Press, USA,1994.
[157]赵敏,胡钰.创新的方法[M].北京:当代中国出版社, 2008.
[158] Song Yuyin, Cai Fuzhi, Zhang Bopeng, et al. One of case-based reasoning product conceptual design systems[J]. Journal of Tsinghua University, 1998, 38 (8) :5-8.
[159] Lee Dongkon , Lee Kyungho. An approach to case-based system for conceptual ship design assistant [J] . Expert Systems with Applications, 1999, 16(1) : 97-104.
[160] Mostow J, Barley M, Weinrich T. Automated reuse of design plans in BOGART[J]. Artificial Intelligence in Engineering Design, 1992, 4 (4) : 181-196.
[161] Rosenman M A, Gero J S, Oxman R E. What’s in a case: the use of case bases, knowledge bases and databases in design[A]. Gerhard N S. Computer Aided Architectural Design Futures - Education, Research, Applications[C]. Friedrich Vieweg & Sohn Verlagsgesellschaft, 1996: 263-277.
[162]台立钢,李殿起,钟廷修,李治.机械产品集成化定制设计与研究[J].机械设计与研究, 2006, 22(01).
[163]贾怀玉,金先龙,李治,蒋爱琴.基于KBE的电梯智能设计系统[J].计算机辅助设计与图形学学报, 2004, 16(6): 861-868.
[164] Chen Xiantao, Zhao Jianghong. A hybrid system approach of case-based reasoning and knowledge-based for product form design[C]. Proceedings of the Third International Conference on Natural Computation (ICNC 2007), 05: 325-330.
[165]孔凡国.机械方案创新设计及其智能支持系统的研究与实践[D].上海交通大学,1997.
[166]冯培恩,徐国荣.基于设计目录的原理方案及其求解过程的特征建模[J].机械工程学报, 1998, 02: 79-86.
[167] Goel A. Design, analogy and creativity[J] . IEEE Expert: Intelligent Systems and Their Applications, 1997, 12(2): 62 - 70.
[168] Qian L, Gero J S. Function-behavior-structure paths and their role in analogy-based design [J] . Artificial Intelligence for Engineering Design , Analysis and Manufacturing–AI EDAM, 1996 , 10(4): 289-312.
[169]陈建国,潘云鹤.基于空间探索的创造性设计方法的研究[J].计算机辅助设计与图形学学报, 2000, 12 (6): 441 - 445.
[170] Umeda Y, Ishii M, Yoshioka M, et al. Supporting conceptual design based on thefunction-behavior-state modeler[J]. Artificial Intelligence for Engineering Design Analysis and Manufacturing-AI EDAM, 1996, 10(4): 275 - 288.
[171] Julie R. J, Ricardo S, Gero J S. Generating innovative designs using qualitive spatial reasoning[C]. Proceedings of the tenth International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), 2005, 2(5).
[172]邓家缇.产品设计的基本理论与技术[J] .中国机械工程, 2000, 11(1/ 2): 139-143.
[173] Campbell M I, Caganj K K. Agent-based synthesis of electromechanical design configurations[J] . Journal of Mechanical Design, 2000, 122(1): 61-69.
[174]赵刚,邓家缇.概念设计自动化系统的演进过程建模[J].计算机集成制造系统, 2001, 7(11): 33-38.
[175]潘云鹤耿卫东.面向智能CAD的分层构造自动型方法[J].软件学报, 1996, 7(5): 280-285.
[176]杨波,黄克正.面向机械产品生长型设计的广义装配原理理论和技术研究[D].济南:山东大学, 2005.
[177]李健,郭连水,邓家缇.用自由度分析法求解装配几何约束满足问题[J].计算机应用, 2000, 20(1): 84-86.
[178] Leizerdwicz W, Lin J, Fox M S. Collaborative design using WWW[C]. Proceedings of WET-ICE’96,CERC,Univesrity of West Virginia, 1996.
[179] Ullman D.G. Mechanical design process[M]. McGraw-Hill, 1997.
[180] Natraj. L. Subramaniam J. Three-dimensional shape searching: state-of-the-art review and future trends [M]. Elsevier Ltd, 2004.
[181]章志勇.三维模型几何相似性比较的研究[D].浙江:浙江大学, 2005.
[182] Ankerst M, Kastenmuller G, Kriegel H P, et al. 3D shape histograms for similarity search and classification in spatial databases [C]. Proceeding of 6th International Symposium on Advance in Spatial Databases[SSD], Hong Kong, China, 1999: 207-228.
[183] Vranic D V, Saupe D. 3D shape descriptor based on 3D Fourier transform[C]. Proceedings of the EURASIP Conference on Digital Signal Processing for Multimedia Communications and Services, 2001: 271-274.
[184] Cornea N D. Curve-skeletons: properties, computation and applications[D]. New Jersey: the State University of New Jersey, 2007.
[185] Dmitriy B, William C, Regli A S. Reeb graph based shape retrieval for CAD [C]. Proceedings ofDETC’03, ASME Design Engineering Technical Conferences, 2003.
[186] Nicu, D C. Curve-skeletons: properties, computation and applications [D]. Rutgers University, 2007.
[187] Ohbuchi R, Nakazawa M, Takei T. Retrieving 3D shapes based on their appearance[C]. Proceeding of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, Berkeley, California, USA, 2003: 39-45.
[188]袁浩,卢章平,骆雪松等.基于极限投影变换的3D模型检索[J].计算机辅助设计与图形学学报, 2007,19(11): 1416-1422.
[189]王飞,张树生,白晓亮等.拓扑和形状特征相结合的三维模型检索[J].计算机辅助设计与图形学学报, 2008, 20(1): 99-103.
[190]马露杰,黄正东,吴青松.基于面形位编码的CAD模型检索[J].计算机辅助设计与图形学学报, 2008, 20(1): 19-25.
[191] Koutsokeras M, Pratikakis I, Miaoulis G. A web-based 3D graphical model search engine[C]. Proceedings of the eighth International Conference on Computer Graphics and Artificial Intelligence, 11-12 May, 2005,Limoges, France: 79-90.
[192]付相君李善平.产品的相似性推理:一种描述逻辑的方法[J].计算机辅助设计与图形学学报, 2006, 18(4): 568-573.
[193]麻芳兰,何玉林,李尚平,苗剑.摩托车智能设计实例推理系统的索引模型[J].计算机集成制造系统, 2006, 12(9): 1379-1416.
[194] Alfredo F. Retrieval of 3D Models using Partial Matching[D]. Portugese: Technical University of Lisbon, 2008.
[195]黎荣,王金诺.基于UG的3D模型相似性评价技术研究[J].计算机工程与应用, 2006, 36: 86-89.
[196] Julie R J, Gero J S. Computational and cognitiuve studies in similarity: evaluating a neural network model of visuo-spatial similarity in design[C]. Gero JS(eds), Studying Designers‘05, 2005.
[197] Julie J, Gero J S. Visual style: qualitative and context dependent categorisation[J]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2006, 20(3): 247–266.
[198] Philip S, Patrick M, Michael K, Thomas F. The Princeton shape benchmark[C]. Shape Modeling International Proceedings of the Shape Modeling, 2004: 167-178.
[199] Patrick M, Halderman A, Michael K, Thomas F. Early experiences with a 3D model search engine[C]. Proceedings of the eighth International Conference on 3D Web Technology on Saint Malo, France, 2003.
[200] Guoyan Yu, Zhen He, Chaoan Lai, Bing Lu. The application of interactive evolutionary algorithm in product design[C]. Intelligent Control and Automation, WCICA 2006, the sixth World Congress on 21-23 June 2006, 2: 6758-6762.
[201] Hiroaki N, Takuya S, Tsuneo K, Kouichi U. Development and evaluation of a 3D graphics design system based on simulated human immune system[C]. Systems, Man and Cybernetics, IEEE International Conference on 2007: 1981-1986.
[202] Walairacht C, Xohara A. Learning mechanism for adaptive fitness function in auto 3D graphics layout using genetic algorithm [C]. Electrical and Computer Engineering, Canadian Conference on 2001, Toronto, Canada, 1: 219-224.
[203] Cvetkovic D, Parmee I C. Preferences and their application in evolutionary multiobjective optimization [C]. Evolutionary Computation, IEEE Transactions on Feb 2002, 6(1): 42–57.
[204] Jeff W K, Gero J S. Can an objective measurement of design protocols reflect the quality of a design outcome [C]. ICED07, Paris, 2007: 1-12.
[205] Gero J S, Vladimir K. Entropic-based similarity and complexity measures of 2D archtectural drawings [J]. Visual and Spatial Reasoning in Design, 2001, 2: 147-161.
[2]刘美华.产品设计原理[M].北京:北京大学出版社,2008: 1-20.
[3]王启广,叶平.现代设计理论[M].徐州:中国矿业大学出版社, 2005:1-10.
[4]王受之.世界现代设计史[M].北京:中国青年出版社,2002,1-17.
[5]梅格斯著,柴常佩译.二十世纪视觉传达设计史[M].武汉:湖北美术出版社,1994:2-13.
[6]奚传绩.设计艺术经典论著选读[M].南京:东南大学出版社,2002:1-25.
[7]安毓英.产品装潢设计百略[M].北京:中国轻工业出版社,1995:5-19.
[8] Gero J S, Neill T M. An approach to the analysis of design protocols[J]. Design Studies, 1998, 19(1): 21-61.
[9]潘云鹤.形状设计思维过程模式[J].浙江大学学报:自然科学版, 1993, 27(3).
[10] Gero J S, Kannengiesser U. Function-behaviour-structure: A model for social situated agents [EB/OL]. http://cs.gmu.edu/~jgero//publications/2003.
[11] Gero J S. Computational models of innovative and creative design processes[J]. Technological Forecasting and Social Change, 2000, 64: 183-196.
[12]唐林.产品概念设计基本原理和方法[M].国防工业出版社,2006.
[13]张建明,魏小鹏,张德珍.产品概念设计的研究现状及其发展方向[J].计算机集成制造系统, 2003, 9(08):613-620.
[14] Pahl G, Beitz W. Engineering design: a systematic approach [M]. Springer Verlag, 1996.
[15]孙守迁,包恩伟,陈蘅,潘云鹤.计算机辅助概念设计研究现状和发展趋势[J].中国机械工程,1999, 03: 105-109.
[16]陈亚华.基于快速设计策略的产品概念设计理论及方法研究[D].重庆大学, 2002.
[17]赵文辉,李思昆.电子产品并行设计方法及虚拟原型仿真环境研究[D].长沙:国防科技大学, 2002.
[18]刘雄飞,王逢瑚.基于网络的交互式虚拟室内环境的研究与实现[D].东北林业大学, 2006.
[19]霍志濮,黄克正.机电系统虚实一体化的创新设计自动化理论与技术研究[D].山东大学,2007.
[20]徐延宁,孟祥旭.虚拟样机建模技术与协同装配方法研究[D].山东大学,2006.
[21]郭万林.机械产品全生命周期设计[J].中国机械工程, 2002, 13(13):1153-1158.
[22]徐志刚,刘维民.设计自动化的深刻内涵与广义外延[J].机械设计, 2002, 6(19).
[23]王艳东,黄克正.以人为原型的设计自动化理论和技术研究[D].山东大学,2006.
[24]高常青,黄克正,张勇.基于能量转换的机械产品概念设计自动化研究与实现[J].中国机械工程, 2007, 18(06).
[25]徐志刚,周以齐,刘庆亮,艾兴.产品结构创新设计自动化理论及CAD系统构造[J].中国机械工程, 2001, 12(08).
[26]龚勉,赵波.超变量几何相关性技术WAVE及应用[J].机械设计, 2004, 21(12).
[27]曹春红,李文辉.几何约束求解技术的研究[D].吉林大学, 2005.
[28] Fang Weidong, Tang Ming Xi, Frazer J H. Constructing an intelligent collaborative design environment with distributed agents[C]. Computer Supported Cooperative Work in Design, The 8th International Conference on 26-28 May 2004, 1: 329 - 335.
[29]王安麟,姜涛,刘广军.智能设计[M].北京:高等教育出版社,2008:1-36.
[30] Hoile C, Tateson R. Design by morphogenesis[J]. BT Technology Journal, 2000, 18(4) : 112-121.
[31] Beurier G, Michel F, Ferber J. A morphogenesis model for multiagent embryogeny[C]. The Tenth International Conference on the Simulation and Synthesis of Living Systems, Cambridge, MA, 2006: 84-90.
[32] Kumar S, Bentley P J. The ABCs of evolutionary design: investigating the evolvability of embryogenies for morphogenesis[C].In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-1999, Morgan Kaufmann Publishers, July 1999: 164-170.
[33] Kumar S. Implicit evolvability: an investigation into the evolvability of an embryogeny[C]. 14 Evolutionary Computation Conference (GECCO 2000), July 8-12, 2000, Las Vegas.
[34] Bentley P J, Wakefield J P. Overview of a generic evolutionary design system[C].In Proceedings of the 2nd On-line Workshop on Evolutionary Computation (WEC2), 1996, Nagoya University, Japan.
[35] Parmee I C. Evolutionary and adaptive strategies for engineering design - an overall framework[C]. Evolutionary Computation, IEEE International Conference on 13-16 Apr. 1997: 373– 378.
[36] Bentley P J, Jonathan P W. The table: an illustration of evolutionary design using genetic algorithms[C]. Genetic Algorithms in Engineering Systems: Innovations and Applications, First International Conference on 12-14 Sep. 1995: 412-418.
[37] Bentley P J, Jonathan P. W. Conceptual evolutionary design by a genetic algorithm[J]. Engineering Design Automation, 1997, 3(2): 119-131.
[38]谭建荣冯毅雄.设计知识建模、演化与应用[M].北京:国防工业出版社,2007: 1-30.
[39] Gero J S. Situated design computing: principles[M]. Topping B H V. (Editor). Civil Engineering Computations: Tools and Techniques, Saxe-Coburg Publications, 2007: 123-132.
[40] Gero J S. Computational models of creative designing based on situated cognition [C]. Proceedings of the 4th conference on Creativity & cognition, Loughborough, UK, 13-16/10/2002: 3-10.
[41] Kan J W, Gero J S. Acquiring information from linkography in protocol studies of designing[C]. International Conference on Engineering Design, ICED’07, 28–31/8/2007, Paris, France.
[42] Bilda Z, Gero J S. Does sketching off-load visuo-Spatial working memory[M]. Studying Designers'05, Key Centre of Design Comp & Cogntn, 2005.
[43] Kan J W. Using the FBS ontology to capture semantic design information in design protocol studies[C]. DTRS7: Design Meeting Protocols, 19-21/9/2007, London, UK.
[44] Sosa R, Gero J S. A computational study of creativity in design: the role of society[J]. AI EDAM: Artificial Intelligence for Engineering Design, Analysis, and Manufactoring, 2005, 19(4): 229-244.
[45] Bentley P J, Sanjeev K. Three ways to grow designs: A comparison of embryogenies for an evolutionary design problem[C]. Genetic and Evolutionary Computation Conference (GECCO'99), Morgan Kaufmann Publishers, Orlando, Florida, USA: 35-43.
[46] Tina Yu, Bentley P J. Methods to evolve legal phenotypes[C].Proceedings of the Fifth Int. Conf. on Parallel Problem Solving From Nature, Amsterdam, 27-30 Sept, 1998: 280-291.
[47] Meng Q C, Feng T J, Zhou C J, Bo J H. Genetic algorithms encoding study and a sufficient convergence condition of Gas [C].Systems, Man and Cybernetics, IEEE International Conference on 10/12/-10/15/1999, Tokyo, Japan, 1: 649-652.
[48]周开俊,李东波,童一飞.面向产品创新设计的功能模块划分方法[J].计算机辅助设计与图形学学报, 2007, 19(1): 73-83.
[49]邓益民,郑堤.机电产品功能与行为表达方法综述[J].工程设计学报, 2008, 3.
[50] Robert J.S.著,杨炳钧,陈燕,邹枝玲,译.认知心理学[M].北京:中国轻工业出版社,2006:83-110.
[51] Gero, J S. Design prototypes: a knowledge representation schema for design[J]. AI Magazine, 1990, 11(4): 26-36.
[52]彭颖红,胡洁. KBE及其在产品设计中的应用[M].上海:上海交通大学出版社,2007: 94-140.
[53]张三元,孙守迁,潘云鹤.基于产品反求工程的产品创新设计方法[J].计算机辅助设计与图形学学报, 2000, 11.
[54]张建明,魏小鹏,张德珍.产品概念设计的研究现状及其发展方向[J].计算机集成制造系统, 2003, 9(08):2-9.
[55]徐宗本,张讲社,郑亚林.计算智能中的仿生学:理论与算法[M].北京:科学出版社,2007:107-160.
[56] Simon H. Neural networks: A comprehensive foundation (Second Edition) [M]. Prentice Hall, 1999.
[57] Ham F M, Kostanie I. Priciples of neuro computing for science & engineering [M]. McGraw Hill, 2001.
[58]张德丰. MATLAB神经网络应用设计[M].北京:机械工业出版社,2009: 157-179.
[59]赵涛.管理学常用方法[M].天津:天津大学出版社,2006:314-327.
[60]李春葆.数据结构教程[M].北京:清华大学出版社,2006,131-166.
[61]景振毅,张泽兵,董霖. MATLAB 7.0实用宝典[M].北京:中国铁道出版社,2009:53-78.
[62]刘弘.支持产品创新的协同设计系统研究技术报告[R].济南:山东师范大学,2006.
[63] Gero J S. AI EDAM at 2000: artificial intelligence in designing[J]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2007, 21: 17–18.
[64]周济.机械设计专家系统概论[M].武汉:华中理工大学出版社,1989.
[65]蔡自兴.人工智能及其应用[M].北京:清华大学出版社, 2005.
[66]张丽平,胡上序.粒子群优化算法的理论和实践[D].浙江大学, 2005.
[67]高隽.智能信息处理方法导论[M].北京:机械工业出版社, 2004.
[68]邢文训,谢金星.现代优化计算方法[M].北京:清华大学出版社, 2005.
[69]危辉,潘云鹤.从知识表示到表示:人工智能认识论上的进步[J].计算机研究与发展, 2000, 37(7):819-825.
[70]苏宝华.面向大量定制生成的产品建模理论、方法及其应用研究[D].杭州:浙江大学,1998.
[71] John M U. A STEP-based object-oriented product model for process planning[J]. Computers ind. Engng., 1996, 31(1/2): 185-188.
[72] Ping Yi Chao, Shen Chout Yeh. Representation of standard mechanical components in a STEP-based product data management system[J]. International Journal of Computer Applications in Technology, 1999, 12(1): 16-26.
[73]何小朝,沈梅,张铁昌.并行CAD/CAM集成中的产品模型表示方法研究[J].航空学报,2000,21(1): 43-47.
[74]王琪,刘永贤,刘彪.协同设计环境下的产品造型技术[J].制造技术与机床, 2006, 9.
[75]欧松,周其节. CIMS环境下的产品设计自动化研究[D].华南理工大学, 1997.
[76] Peak R S, Fulton R E, Nishigaki I, Okamoto N. Integrating engineering design and analysis using a multi-representation approach[J]. Engineering with Computers, 1998, 14(2): 93-114.
[77] Lee J Y. Shape representation and interoperability for virtual prototyping in a distributed design environment[J]. International journal of advanced manufacturing technology, ISSN 0268-3768, 2001, 17(6): 425-434.
[78]唐文献,方明伦. KBE环境下面向协同创新的产品开发支持系统研究[D].上海大学,2003.
[79]陈磊,叶修梓.异构CAD产品模型的数据分层表示及重用技术研究[D].浙江大学, 2008.
[80] Horvath L, Rudas I J. Evaluation of Petri net process model representation as a tool of virtual manufacturing[C]. Systems, Man and Cybernetics, IEEE International Conference on 11-14 Oct 1998, 1: 178 - 183.
[81] Case K, Harun W A W. Feature-based representation for manufacturing planning[J]. International Journal of Production Research, 2000, 38(17): 4285-4300.
[82] Tallinen T, Osuna R V, Lastra J L M, Tuokko R. Product model representation concept for the purpose of assembly process modeling[C]. Assembly and Task Planning, the IEEE International Symposium on 10-11 July 2003: 222–227.
[83] Jabbour T, Mascle C, Maranzana R. A database for the representation of assembly features in mechanical products[J]. International Journal of Computational Geometry and Apllications, 1998, 8(5): 483-509.
[84]刘晓冰,袁长峰,邢英杰,王万雷.基于类和特征的产品配置建模[J].计算机集成制造系统, 2005, 11(8): 1057-1063.
[85]谢清,谭建荣,冯毅雄.面向配置设计的产品功构建模方法[J].计算机辅助设计与图形学学报, 2006, 18(4): 574-579.
[86] Pierre D L. An assembly-oriented product family representation for integrated design[J]. IEEE transactions on robotics and automation, ISSN 1042-296X , 2003, 19(1): 75-88.
[87] Kusiak A, Chun-Che Huang. Development of modular products[J]. Components, Packaging and Manufacturing Technology, Part A, IEEE Transactions on Dec 1996, 19(4): 523–538.
[88]姜大志,孙俊兰.成组技术在产品快速设计系统中的应用[J].机械设计, 2005, 22(8): 57-59.
[89]王启富杨磊黄运保王波兴.协同产品开发中的产品模型轻量化技术[J].计算机辅助设计与图形学学报, 2006, 18(01):108-113.
[90] Mehalawi R, Allen M. A database system of mechanical components based on geometric and topological similarity, Part I: representation[J]. Computer-Aided Design, 2003, 35(1): 83-94.
[91]刘云华,刘俊,陈立平.产品三维数据模型轻量化表示实现[J].计算机辅助设计与图形学学报, 2006, 18(04).
[92] Yongmin Zhong, Mueller-Wittig W, Weiyin Ma. A model representation for solid modeling in a virtual reality environment[C]. Shape Modeling International Proceedings, 2002: 183–190.
[93]王靖滨,俞杰,耿卫东,潘云鹤.基于FBS的产品创新设计模型[J].计算机辅助设计与图形学学报, 2000, 12(11): 824-826.
[94]宋慧军,林志航,罗时飞.机械产品概念设计中的知识表示[J].计算机辅助设计与图形学学报, 2003, 15(4): 438-443.
[95]张帅,冯培恩.复合功能产品概念设计建模理论及自动化求解方法研究[D].浙江大学,2005.
[96]付相君,李善平,郭鸣.产品数据模型的本体知识表达[J].计算机辅助设计与图形学学报, 2005, 17(3): 570-577.
[97]邹光明,胡于进,王兴东,孔建益.概念设计产品表示模型研究[J].武汉科技大学学报(自然科学版), 2008, 31(02).
[98]欧阳渺安.面向对象的智能产品建模技术的研究[J].现代制造工程, 2005, 06: 40-42.
[99]张帅,冯培恩,潘双夏,陈泳,朱爱华.基于循环映射模型的概念设计自动化策略研究[J].计算机辅助设计与图形学学报, 2005, 17(3): 491-497.
[100] Buur J. A theoretical approach to mechatronics design [M]. IK Publisher, 1990.
[101] Schmekel H. Functional models and design solutions[J]. Annals of CIRP, 1989, 38:129-132.
[102] Stone R B, Wood K L, Crawford R H. A heuristic method for identifying modules for product architectures[J]. Design Studies, 2000, 21(1): 5-31.
[103]俞杰,耿卫东,潘云鹤.面向产品创新设计的CAD方法综述[J].计算机辅助设计与图形学学报, 1999, (02).
[104]谭同德,童秉枢,王涛.产品结构设计的数据模型[J].计算机辅助设计与图形学学报, 2000, 12(1): 11-16.
[105]李书田,郑联语,汪叔淳.集成环境中基于特征顺序的产品建模方法研究[J].计算机辅助设计与图形学学报,1999, 11(5): 420-425.
[106] Gero J S, Ricardo S. Complexity measures as a basis for mass customization of novel designs[J]. Environment and Planning B: Planning and Design, 2007, 35(1) : 3– 15.
[107] Bentley P J, Jonathan P W. Generic representation of solid-object geometry for genetic search[J]. Microcomputers in Civil Engineering, 1996, 11(3): 153-161.
[108] Tyson R B. Applying the design structure matrix to system decomposition and integration problems: A review and new directions[J]. Engineering Management, IEEE Transactions on Aug. 2001, 48(3): 292-306.
[109]董雁,谭建荣.结构定性建模理论及其在机械产品类比设计中应用研究[D].浙江大学, 2004.
[110]冯力,叶尚辉.支持机械创新设计CAD方法的探索[D] .西安电子科技大学, 1999.
[111]赵婷婷,魏小鹏.基于直觉启发和改进遗传算法的形状概念设计[D].大连理工大学, 2005.
[112] Sasajima M, Kitamura Y. Presentation language for behavior and function[J]. FBRL-Expert Systems with Application, 1996, 10(3/4): 471-479.
[113] Qian L. Function-behavior-structure paths and their role in analogy-based design[J]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing -AI EDAM, 1996, 10(4): 289-312.
[114]张勇,黄克正.基于同步公差设计的概念结构设计优化[D].山东大学, 2006.
[115]顾正朝,高曙明.并行环境下注塑件智能设计支撑技术研究[J].计算机辅助设计与图形学学报, 1999, 11(1): 39-42.
[116]谢清,谭建荣,冯毅雄.面向配置设计的产品功构建模方法[J].计算机辅助设计与图形学学报, 2006, 18(4): 574-579.
[117]谢来勇,郝永平,张秉权.基于XML的产品信息模型表示及应用[J].计算机集成制造系统, 2004, 10(12): 1492-1496.
[118] Xinqin Gao, Zongbin Li. Computer aided conceptual design of mechanical product using polychromatic sets[C]. Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation, 25-28 June, 2006, Luoyang, China: 1168-1174.
[119] Gero J S, Kazakov V. On measuring the visual complexity of 3D solid objects[J]. Journal of Design Sciences and Technology, 2003, 12(1): 35-44.
[120]余军合,吴昭同.面向全生命周期虚拟产品模型的研究与应用[D].浙江大学, 2002.
[121]蔡自兴.人工智能及其应用[M].北京:清华大学出版社, 2005.
[122]蒋占四,李尚平,邓劲莲.甘蔗收割机械智能设计系统的研究开发[J].计算机辅助设计与图形学学报, 2004, 16(12): 1754-1757.
[123] Zhang W Y, Tors B , Britton G, et al. A knowledge-based expert system for functional design of engineering systems[J]. Engineering with Computers , 2001, 17 (4): 339-353.
[124]王玉新.机械系统概念设计自动化方法[J].机械工程学报, 2002, 38(10):148-153 .
[125]王小同范立础.智能设计系统的IDS模型[J].模式识别与人工智能, 1996, 9(2).
[126]郝泳涛.基于特征编码组和人工神经网络的模式化智能工艺设计系统关键技术研究[D].上海:上海交通大学, 1999.
[127]郝泳涛,赵卫东,李启炎.基于模式化知识和人工神经网络的智能设计系统框架研究[J].计算机辅助设计与图形学学报, 2001, 13(9): 834-839.
[128]钟佩思,高国安.基于神经网络块的混合型方案设计知识库系统[J].机械设计, 1999, 16 (5): 1-2.
[129]杨海军,李敏强.进化计算中的模式理论、涌现及应用研究[D].天津大学, 2004.
[130]李建武,李敏强.遗传算法适应值曲面及遗传算法困难度分析[D].天津大学, 2002.
[131] Sekanina L. Evolutionary algorithms[D]. Brno University, 2005.
[132] Thomas B. Evolutionary computation[M]. IOP Publishing Ltd., 1997.
[133]李敏强,寇纪松.遗传算法的基本理论和应用[M].北京:科学出版社, 2004.
[134]徐宗本,张讲社,郑亚林.计算智能中的仿生学:理论与算法[M].北京:科学出版社, 2007.
[135] Schwefel H P, Kursawe F. On natural life’s tricks to survive and evolve[C]. Evolutionary Computation, IEEE World Congress on Computational Intelligence on 4-9 May 1998: 1-8.
[136] Parmee I C, Bonham C R. Towards the support of innovative conceptual design through interactive evolutionary computing strategies[J]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing– AI EDAM, 2000,14(1): 3-16.
[137]冯培恩,陈泳,张帅等.基于产品基因的概念设计[J] .机械工程学报, 2002, 38(10): 1-6.
[138] Bentley P J. Aspects of evolutionary design by computers[M]. Spinger-Verlag London Limited. UK, 1999.
[139] Rodríguez M A, Jarur M C. A genetic algorithm for searching spatial configurations[C]. Evolutionary Computation, IEEE Transactions on 2005, 9 (3): 252- 270.
[140] Koza J R. Automated synthesis of analog electrical circuits by means of genetic programming[C]. Evolutionary Computation, IEEE Transactions on 1997, 1(2): 109–128.
[141]王小港,姚林声.遗传算法在VLSI设计自动化中的应用研究[D].中国科学院, 2001.
[142] Drechsler R. Evolutionary algorithms for VLSI CAD[M]. Kluwer Academic Publishers, 1998.
[143] Lamas A, Pe?a F, Duro R. Automatic evolutionary design of control systems for underwater vehicles[C]. International Conference on Computational Intelligence for Modelling, Control and Automation and Intelligent Agents, Web Technologies and Internet Commerce on 28 Nov. 2006- 1 Dec. 2006: 157-157.
[144] Krzysztof W, Bentley P J. Optimising the performance of a Formula one car using a genetic algorithm[C]. International conference on parallel problem solving from nature, Birmingham, 18/09/2004: 702-711.
[145]舒启林,郝博.机械产品方案设计自动化研究[J].中国机械工程, 2000, 13(19): 1676-1679.
[146] Richard H. D. Engineering design optimization with genetic algorithms[C]. Northcon Conference Proceedings on 10/21-10/23/1998, Seattle, WA, USA: 114-119.
[147] Tetsushi K, Fumitoshi M, Ranajit C. Proposition of twisting mode of locomotion and GA based motion planning for transition of locomotion modes of 3-dimensional snakelike robot[C]. Robotics and Automation, ICRA’02, IEEE International Conference on 2002, 2: 1507-1512.
[148] Miha K. Genetic algorithm approach for autonomous vehicles[C]. Industrial Technology, IEEE International Conference on 10-12 Dec. 2003, 2: 974–978.
[149] Medina L, Díaz E, Rubio E, Rodríguez K. Design of a planar array of sensors for 3D location using genetic algorithms[C]. Ultrasonics, IEEE Symposium on 5-8 Oct. 2003, 2: 1384–1387.
[150]刘弘,刘希玉.支持外观造型创新设计的进化计算方法[J].计算机辅助设计与图形学学报, 2006, 18(1): 101-107.
[151] Jussi Angesleva. Evolutionary computation in creative design[D]. Berlin University, 2005.
[152]冯毅雄,谭建荣,张树有,马辉.集成环境下创新产品进化设计技术研究[J].计算机集成制造系统, 2006, 12(1): 1-20.
[153] Rieffel John. Evolving assembly plans for fully automated design and assembly[C]. Evolvable Hardware, NASA/DoD Conference on 29 June-1 July 2005: 165-170.
[154] Chocron O, Bidaud P. Genetic design of 3D modular manipulators[C].Robotics and Automation, IEEE International Conference on 20-25 Apr. 1997, 1: 223-228.
[155] Bentley P J, Gordon T, Kim J, Kumar S. New trends in evolutionary computation[C]. Proceedings of Congress on Evolutionary Computation (CEC-2001), Seoul, Korea.
[156] Kumar S, Bentley P J. Computational embryology: past, present and future[M]. MIT Press, USA,1994.
[157]赵敏,胡钰.创新的方法[M].北京:当代中国出版社, 2008.
[158] Song Yuyin, Cai Fuzhi, Zhang Bopeng, et al. One of case-based reasoning product conceptual design systems[J]. Journal of Tsinghua University, 1998, 38 (8) :5-8.
[159] Lee Dongkon , Lee Kyungho. An approach to case-based system for conceptual ship design assistant [J] . Expert Systems with Applications, 1999, 16(1) : 97-104.
[160] Mostow J, Barley M, Weinrich T. Automated reuse of design plans in BOGART[J]. Artificial Intelligence in Engineering Design, 1992, 4 (4) : 181-196.
[161] Rosenman M A, Gero J S, Oxman R E. What’s in a case: the use of case bases, knowledge bases and databases in design[A]. Gerhard N S. Computer Aided Architectural Design Futures - Education, Research, Applications[C]. Friedrich Vieweg & Sohn Verlagsgesellschaft, 1996: 263-277.
[162]台立钢,李殿起,钟廷修,李治.机械产品集成化定制设计与研究[J].机械设计与研究, 2006, 22(01).
[163]贾怀玉,金先龙,李治,蒋爱琴.基于KBE的电梯智能设计系统[J].计算机辅助设计与图形学学报, 2004, 16(6): 861-868.
[164] Chen Xiantao, Zhao Jianghong. A hybrid system approach of case-based reasoning and knowledge-based for product form design[C]. Proceedings of the Third International Conference on Natural Computation (ICNC 2007), 05: 325-330.
[165]孔凡国.机械方案创新设计及其智能支持系统的研究与实践[D].上海交通大学,1997.
[166]冯培恩,徐国荣.基于设计目录的原理方案及其求解过程的特征建模[J].机械工程学报, 1998, 02: 79-86.
[167] Goel A. Design, analogy and creativity[J] . IEEE Expert: Intelligent Systems and Their Applications, 1997, 12(2): 62 - 70.
[168] Qian L, Gero J S. Function-behavior-structure paths and their role in analogy-based design [J] . Artificial Intelligence for Engineering Design , Analysis and Manufacturing–AI EDAM, 1996 , 10(4): 289-312.
[169]陈建国,潘云鹤.基于空间探索的创造性设计方法的研究[J].计算机辅助设计与图形学学报, 2000, 12 (6): 441 - 445.
[170] Umeda Y, Ishii M, Yoshioka M, et al. Supporting conceptual design based on thefunction-behavior-state modeler[J]. Artificial Intelligence for Engineering Design Analysis and Manufacturing-AI EDAM, 1996, 10(4): 275 - 288.
[171] Julie R. J, Ricardo S, Gero J S. Generating innovative designs using qualitive spatial reasoning[C]. Proceedings of the tenth International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), 2005, 2(5).
[172]邓家缇.产品设计的基本理论与技术[J] .中国机械工程, 2000, 11(1/ 2): 139-143.
[173] Campbell M I, Caganj K K. Agent-based synthesis of electromechanical design configurations[J] . Journal of Mechanical Design, 2000, 122(1): 61-69.
[174]赵刚,邓家缇.概念设计自动化系统的演进过程建模[J].计算机集成制造系统, 2001, 7(11): 33-38.
[175]潘云鹤耿卫东.面向智能CAD的分层构造自动型方法[J].软件学报, 1996, 7(5): 280-285.
[176]杨波,黄克正.面向机械产品生长型设计的广义装配原理理论和技术研究[D].济南:山东大学, 2005.
[177]李健,郭连水,邓家缇.用自由度分析法求解装配几何约束满足问题[J].计算机应用, 2000, 20(1): 84-86.
[178] Leizerdwicz W, Lin J, Fox M S. Collaborative design using WWW[C]. Proceedings of WET-ICE’96,CERC,Univesrity of West Virginia, 1996.
[179] Ullman D.G. Mechanical design process[M]. McGraw-Hill, 1997.
[180] Natraj. L. Subramaniam J. Three-dimensional shape searching: state-of-the-art review and future trends [M]. Elsevier Ltd, 2004.
[181]章志勇.三维模型几何相似性比较的研究[D].浙江:浙江大学, 2005.
[182] Ankerst M, Kastenmuller G, Kriegel H P, et al. 3D shape histograms for similarity search and classification in spatial databases [C]. Proceeding of 6th International Symposium on Advance in Spatial Databases[SSD], Hong Kong, China, 1999: 207-228.
[183] Vranic D V, Saupe D. 3D shape descriptor based on 3D Fourier transform[C]. Proceedings of the EURASIP Conference on Digital Signal Processing for Multimedia Communications and Services, 2001: 271-274.
[184] Cornea N D. Curve-skeletons: properties, computation and applications[D]. New Jersey: the State University of New Jersey, 2007.
[185] Dmitriy B, William C, Regli A S. Reeb graph based shape retrieval for CAD [C]. Proceedings ofDETC’03, ASME Design Engineering Technical Conferences, 2003.
[186] Nicu, D C. Curve-skeletons: properties, computation and applications [D]. Rutgers University, 2007.
[187] Ohbuchi R, Nakazawa M, Takei T. Retrieving 3D shapes based on their appearance[C]. Proceeding of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, Berkeley, California, USA, 2003: 39-45.
[188]袁浩,卢章平,骆雪松等.基于极限投影变换的3D模型检索[J].计算机辅助设计与图形学学报, 2007,19(11): 1416-1422.
[189]王飞,张树生,白晓亮等.拓扑和形状特征相结合的三维模型检索[J].计算机辅助设计与图形学学报, 2008, 20(1): 99-103.
[190]马露杰,黄正东,吴青松.基于面形位编码的CAD模型检索[J].计算机辅助设计与图形学学报, 2008, 20(1): 19-25.
[191] Koutsokeras M, Pratikakis I, Miaoulis G. A web-based 3D graphical model search engine[C]. Proceedings of the eighth International Conference on Computer Graphics and Artificial Intelligence, 11-12 May, 2005,Limoges, France: 79-90.
[192]付相君李善平.产品的相似性推理:一种描述逻辑的方法[J].计算机辅助设计与图形学学报, 2006, 18(4): 568-573.
[193]麻芳兰,何玉林,李尚平,苗剑.摩托车智能设计实例推理系统的索引模型[J].计算机集成制造系统, 2006, 12(9): 1379-1416.
[194] Alfredo F. Retrieval of 3D Models using Partial Matching[D]. Portugese: Technical University of Lisbon, 2008.
[195]黎荣,王金诺.基于UG的3D模型相似性评价技术研究[J].计算机工程与应用, 2006, 36: 86-89.
[196] Julie R J, Gero J S. Computational and cognitiuve studies in similarity: evaluating a neural network model of visuo-spatial similarity in design[C]. Gero JS(eds), Studying Designers‘05, 2005.
[197] Julie J, Gero J S. Visual style: qualitative and context dependent categorisation[J]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2006, 20(3): 247–266.
[198] Philip S, Patrick M, Michael K, Thomas F. The Princeton shape benchmark[C]. Shape Modeling International Proceedings of the Shape Modeling, 2004: 167-178.
[199] Patrick M, Halderman A, Michael K, Thomas F. Early experiences with a 3D model search engine[C]. Proceedings of the eighth International Conference on 3D Web Technology on Saint Malo, France, 2003.
[200] Guoyan Yu, Zhen He, Chaoan Lai, Bing Lu. The application of interactive evolutionary algorithm in product design[C]. Intelligent Control and Automation, WCICA 2006, the sixth World Congress on 21-23 June 2006, 2: 6758-6762.
[201] Hiroaki N, Takuya S, Tsuneo K, Kouichi U. Development and evaluation of a 3D graphics design system based on simulated human immune system[C]. Systems, Man and Cybernetics, IEEE International Conference on 2007: 1981-1986.
[202] Walairacht C, Xohara A. Learning mechanism for adaptive fitness function in auto 3D graphics layout using genetic algorithm [C]. Electrical and Computer Engineering, Canadian Conference on 2001, Toronto, Canada, 1: 219-224.
[203] Cvetkovic D, Parmee I C. Preferences and their application in evolutionary multiobjective optimization [C]. Evolutionary Computation, IEEE Transactions on Feb 2002, 6(1): 42–57.
[204] Jeff W K, Gero J S. Can an objective measurement of design protocols reflect the quality of a design outcome [C]. ICED07, Paris, 2007: 1-12.
[205] Gero J S, Vladimir K. Entropic-based similarity and complexity measures of 2D archtectural drawings [J]. Visual and Spatial Reasoning in Design, 2001, 2: 147-161.