纸币清分机产品族设计过程配置优化方法研究
|
摘要
在日益激烈的国际市场竞争环境中,金融机具行业企业面临着尽快提供适合不同层次和群体的产品设计问题。纸币清分机是金融领域现金处理业务的高端必备设备,具有结构复杂、智能化程度高、市场需求变化快的特点。
本文针对面向大批量定制的纸币清分机产品族设计过程中一些关键问题进行了深入研究,目的是以最快的速度和最低的成本为客户设计出满足个性化需求的产品,结合纸币清分机开发过程特点,应用产品族设计理论,详细阐述了纸币清分机产品族设计开发过程,并提出了产品族设计过程的配置优化方法,并对研究成果进行了验证和应用。本文的主要研究内容叙述如下：
(1)应用基于设计公理的产品族设计理论提出纸币清分机产品族设计过程。建立产品开发过程的多视图模型和任务结构模型,实现任务结构模型到Petri网模型的映射定义并进一步推导与工作流网的映射转换关系,结合纸币清分机的设计开发过程完成了任务结构模型到工作流网的转化并进行了实例验证分析。
(2)提出一种面向产品族设计的纸币清分机产品平台核心模块的确定方法。通过建立纸币清分机产品的模块关联矩阵,采用变个体长度的混合蛙跳算法优化模糊聚类数和聚类中心,求得产品平台构成模块的最优模糊划分,并应用切断算子和拼接算子对个体进行重组形成新个体并进行局部寻优,解决模糊C均值聚类局部极小值和初始化选值敏感性问题。在纸币清分机产品族平台设计中进行了仿真验证,实现纸币清分机模块化产品族公共平台和核心模块的有效确定。
(3)提出了产品族设计过程中产品族配置性能预测方法。在基于递阶支持向量机的配置综合性能预测方法框架下对纸币清分机产品族的历史数据库进行数据挖掘,预测新配置产品的性能,提出一种改进混合蛙跳算法来优化SVM模型的核函数参数和误差惩罚因子,应用模拟退火算法提高算法的局部搜索能力和收敛速度,通过以纸币清分机产品族为实例的仿真实验并对比其他方法验证所提预测方法的有效性,为准确、快速地进行纸币清分机产品族配置提供了有效方法,满足多样化的客户需求。
The financial machinery enterprises are facing with the problem providing proper product design for different kinds of customers especially under the increasingly fierce competition in the international market. The currency sorting machine is important and necessary cash processing equipment in the financial industry. It has the characteristics of complex structure, intelligence and changing demand.
In order to meet the personalized products demand as quickly as possible and at the lowest cost, the dissertation carried out an in-depth research on some key problems of the product family design of banknote sorting machine in the process of design for mass customization. The dissertation presents new methods combining banknote sorting machine structure, design features and development processes. The research findings are applied successfully in practice. The main research contents in this dissertation are described as follows:
(1) The development process of banknote sorting machine is analyzed in detail taking into account product structure and features based on the product family design-oriented theory and key technology. The multi-views modeling method and the task structures in the product development process are proposed. The mapping mechanism from the task structure of the product development process to the workflow net is set up. The design verification results of banknote sorting machine development process based on WF-NET show that the proposed method can effectively realize the task distribution and performance estimation for analysis the product development cycle accurately and quantitatively.
(2) The research on the method for determining product platform design modules in the process of modularized product family design is carried out based on fuzzy C-means (FCM) clustering algorithm optimized by the improved shuffled frog leaping algorithm (SFLA). The component coefficient matrix based on the datum collected is set up. The number of fuzzy clustering and cluster centers are optimized by sizable-individual SFLA to obtain the optimized fuzzy partition of the components. The simulation results of the product family design of the banknote sorting machine show that the proposed method supplies the theory basis of the quantity mathematic analysis and fast configuration for the product family design.
(3) A method of product family configuration performance prediction is proposed in the process of product design. The new variant product performances are predicted through the data mining on the historical datum of banknote sorting machine product family under the framework of configuration comprehensive performance prediction method based on SVM. An improved shuffled frog leaping algorithm (SFLA) is adopted to optimize the kernel function parameters and error penalty factors of the SVM models, where the simulated annealing algorithm is used to increase local searching ability and convergence velocity.
Finally, the proposed method is verified on a newly developed module-based banknote sorting machine product family to assess the effectiveness of predicting the configuration performances of the module-based product family design accurately and quickly.
本文针对面向大批量定制的纸币清分机产品族设计过程中一些关键问题进行了深入研究,目的是以最快的速度和最低的成本为客户设计出满足个性化需求的产品,结合纸币清分机开发过程特点,应用产品族设计理论,详细阐述了纸币清分机产品族设计开发过程,并提出了产品族设计过程的配置优化方法,并对研究成果进行了验证和应用。本文的主要研究内容叙述如下：
(1)应用基于设计公理的产品族设计理论提出纸币清分机产品族设计过程。建立产品开发过程的多视图模型和任务结构模型,实现任务结构模型到Petri网模型的映射定义并进一步推导与工作流网的映射转换关系,结合纸币清分机的设计开发过程完成了任务结构模型到工作流网的转化并进行了实例验证分析。
(2)提出一种面向产品族设计的纸币清分机产品平台核心模块的确定方法。通过建立纸币清分机产品的模块关联矩阵,采用变个体长度的混合蛙跳算法优化模糊聚类数和聚类中心,求得产品平台构成模块的最优模糊划分,并应用切断算子和拼接算子对个体进行重组形成新个体并进行局部寻优,解决模糊C均值聚类局部极小值和初始化选值敏感性问题。在纸币清分机产品族平台设计中进行了仿真验证,实现纸币清分机模块化产品族公共平台和核心模块的有效确定。
(3)提出了产品族设计过程中产品族配置性能预测方法。在基于递阶支持向量机的配置综合性能预测方法框架下对纸币清分机产品族的历史数据库进行数据挖掘,预测新配置产品的性能,提出一种改进混合蛙跳算法来优化SVM模型的核函数参数和误差惩罚因子,应用模拟退火算法提高算法的局部搜索能力和收敛速度,通过以纸币清分机产品族为实例的仿真实验并对比其他方法验证所提预测方法的有效性,为准确、快速地进行纸币清分机产品族配置提供了有效方法,满足多样化的客户需求。
The financial machinery enterprises are facing with the problem providing proper product design for different kinds of customers especially under the increasingly fierce competition in the international market. The currency sorting machine is important and necessary cash processing equipment in the financial industry. It has the characteristics of complex structure, intelligence and changing demand.
In order to meet the personalized products demand as quickly as possible and at the lowest cost, the dissertation carried out an in-depth research on some key problems of the product family design of banknote sorting machine in the process of design for mass customization. The dissertation presents new methods combining banknote sorting machine structure, design features and development processes. The research findings are applied successfully in practice. The main research contents in this dissertation are described as follows:
(1) The development process of banknote sorting machine is analyzed in detail taking into account product structure and features based on the product family design-oriented theory and key technology. The multi-views modeling method and the task structures in the product development process are proposed. The mapping mechanism from the task structure of the product development process to the workflow net is set up. The design verification results of banknote sorting machine development process based on WF-NET show that the proposed method can effectively realize the task distribution and performance estimation for analysis the product development cycle accurately and quantitatively.
(2) The research on the method for determining product platform design modules in the process of modularized product family design is carried out based on fuzzy C-means (FCM) clustering algorithm optimized by the improved shuffled frog leaping algorithm (SFLA). The component coefficient matrix based on the datum collected is set up. The number of fuzzy clustering and cluster centers are optimized by sizable-individual SFLA to obtain the optimized fuzzy partition of the components. The simulation results of the product family design of the banknote sorting machine show that the proposed method supplies the theory basis of the quantity mathematic analysis and fast configuration for the product family design.
(3) A method of product family configuration performance prediction is proposed in the process of product design. The new variant product performances are predicted through the data mining on the historical datum of banknote sorting machine product family under the framework of configuration comprehensive performance prediction method based on SVM. An improved shuffled frog leaping algorithm (SFLA) is adopted to optimize the kernel function parameters and error penalty factors of the SVM models, where the simulated annealing algorithm is used to increase local searching ability and convergence velocity.
Finally, the proposed method is verified on a newly developed module-based banknote sorting machine product family to assess the effectiveness of predicting the configuration performances of the module-based product family design accurately and quickly.
引文
[1]Paul Schonsleben. Methods and tools that support a fast and efficient design-to-order process for parameterized product families [J]. CIRP Annals-Manufacturing Technology, 2012,61(1):179-182.
[2]王爱民,肖天元,孟明辰.面向大规模定制的配置设计技术研究[J].计算机集成制造系统,2004,10(11)：1326-1337.
[3]Simpson T W, Maier J R A, Mistree F. Product platform design:method and application [J]. Research in Engineering Design,2001,13(1):2-22.
[4]Jiao J X, Tseng M M, Vincent G. Duffy, Fuhua Lin. Product family modeling for mass customization[J]. Computers & Industrial Engineering,1998,35(3-4):495-498.
[5]Tseng M M, Jiao J X. A variant approach to product definition by recognizing functional requirement patterns [J]. Journal of Engineering Design,1997,8(4):329-340.
[6]Bimal Nepal, Leslie Monplaisir, Oluwafemi Famuyiwa. Matching product architecture with supply chain design [J]. European Journal of Operational Research,2012,216(2): 312-325.
[7]Egon Ostrosi, Alain-Jerome Fougeres, Michel Ferney. Fuzzy agents for product configuration in collaborative and distributed design process [J]. Applied Soft Computing,2012,12(8):2091-2105.
[8]Carlos Alberto Costa, Marcos Alexandre Luciano, Celson Pantoja Lima, Robert I. M. Young. Assessment of a product range model concept to support design reuse using rule based systems and case based reasoning [J]. Advanced Engineering Informatics,2012,26(2): 292-305.
[9]Adam L Chen, Daniel H Martinez. A heuristic method based on genetic algorithm for the baseline-product design [J]. Expert Systems with Applications,2012,39(5): 5829-5837.
[10]E Francalanza, J C Borg, C L Constantinescu. A Case for Assisting'Product Family' Manufacturing System Designers [J]. Procedia CIRP,2012,3:376-381.
[11]Yaser Ghanam, Frank Maurer, Pekka Abrahamsson. Making the leap to a software platform strategy:Issues and challenges [J]. Information and Software Technology,2012,54(9): 968-984.
[12]D Xue, G Hua, V Mehrad, P Gu. Optimal adaptable design for creating the changeable product based on changeable requirements considering the whole product life-cycle [J]. Journal of Manufacturing Systems,2012,31 (1):59-68.
[13]Jiao J, Simpson T W, Siddique Z. Product family design and platform-based product development:a state-of-theart review [J]. Journal of Intelligent Manufacturing,2007, 18(1):5-29.
[14]Dong Yang, Ming Dong. A constraint satisfaction approach to resolving product configuration conflicts [J]. Advanced Engineering Informatics,2012,26(3):592-602.
[15]H Panetto, M Dassisti, A Tursi. ONTO-PDM:Product-driven ONTOlogy for Product Data Management interoperability within manufacturing process environment [J]. Advanced Engineering Informatics,2012,26(2):334-348.
[16]Thevenot H J, Simpson T W. Commonality indices for product family design:a detailed Comparison [J]. Journal of Engineering Design,2006,17(2):99-119.
[17]刘晓冰,董建华,孙伟.面向产品族的建模技术研究[J].计算机辅助设计与图形学学报,2001,13(7)：636-641.
[18]王爱民,孟明辰,黄靖远.面向产品族规划的核心平台数学描述及确定方法[J].清华大学学报(自然科学版),2002,42(8)：1049-1052.
[19]李占山,寇飞宏,欧阳丹彤.产品配置器的研究进展[J].吉林大学学报(自然科学版),2006,44(3)：429-438.
[20]Zheng L Y, Dong H F, Vichare P, et al. Systematic modeling and reusing of process knowledge for rapid process configuration [J]. Robotics and Computer-Integrated Manufacturing,2008,24(6):763-772.
[21]叶世琴,但斌.大规模定制产品族模块定制属性分析模型[J].工业工程,2007,10(6)：72-75.
[22]Michael D. Johnson, Randolph E. Kirchain. Quantifying the effects of product family decisions on material selection:A process-based costing approach[J]. International Journal of Production Economics,2009,120(2):653-668.
[23]赵燕伟,苏楠,张峰等.基于可拓实例推理的产品族配置设计方法[J].机械工程学报,2010,46(15)：146-154.
[24]伊辉勇,刘伟.基于顾客满意度的在线定制产品族规模优化[J].工业工程与管理,2011,16(6)：55-59.
[25]Messac A, Martinez M, Simpson T. Effective product family design using physical programming [J]. Engineering Optimization,2002,34(3):245-261.
[26]Messac A, Martinez M, Simpson T. Introduction of a product family penalty function using physical programming [J]. Journal of Mechanical Design,2002,124(2):164-172.
[27]Jacques Lamothe, Khaled Hadj-Hamou, Michel Aldanondo. An optimization model for selecting a product family and designing its supply chain[J]. European Journal of Operational Research,2006,169(3):1030-1047.
[28]高卫国,徐燕申,陈永亮等.广义模块化设计原理及方法[J].机械工程学报,2007,43(6)：48-54.
[29]Galan R, Racero J, Eguia I, Garcia J M. A systematic approach for product families formation in Reconfigurable Manufacturing Systems[J]. Robotics and Computer-Integrated Manufacturing,2007,23(5):489-502.
[30]万雪峰,但斌,经有国.在线大规模定制下基于客户需求模板的产品配置研究[J].工业工程,2010,13(4)：69-73.
[31]Elmaraghy H, Azab A, Schuh G, et al. Managing variations in products, processes and manufacturing systems [J]. CIRP Annals-Manufacturing Technology,2009,58(1): 441-446.
[32]郑联语,纪录.产品族工装配置技术研究与实现[J].计算机集成制造系统,2011,17(3)：585-594.
[33]雒兴刚,杨勇.基于联合分析的可配置产品优化选择方法[J].中国机械工程,2012,23(5)：578-584.
[34]侯亮,唐任仲,徐燕申.产品模块化设计理论、技术与应用研究进展[J].机械工程学报,2004,40(1)：56-61.
[35]张换高,赵文燕,江屏等.基于相似性与结构敏感性分析的产品平台设计过程模型[J].机械工程学报,2012,48(11)：104-118.
[36]Timothy Simpson, Bryan D'Souza. Assessing variable levels of platform commonality within a product family using a multiobjective genetic algorithm [C]//Proceedings of the 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, September 4-6,2002, Atlanta, Georgia. USA:AIAA, c2002:1-17.
[37]张利.大批量定制模型的客户驱动参数映射与描述结构研究[J].合肥工业大学学报(自然科学版),2003,26(6)：1152-1156.
[38]秦红斌,肖人彬,陈义保等.面向公共产品平台通用化的聚类分析方法研究[J].计算机辅助设计与图形学学报,2004,16(4)：518-522.
[39]Wheelwright Steven C, Clark Kim B. Creating project plans to focus product development [J]. Harvard Business Review,1992,70(2):67-83.
[40]王爱民,肖田元,范莉娅等.面向产品族的制造单元聚类规划研究[J].计算机集成制造系统,2004,10(10)：1257-1261.
[41]王爱民,肖田元,赵银燕等.面向产品族模块化设计和制造的工艺聚类分析方法[J].清华大学学报(自然科学版),2004,44(10)：1394-1397.
[42]孙国梓,郁鼎文,吴志军.个性化配置器的粗糙集方法研究[J].计算机集成制造系统,2005,11(2)：168-172.
[43]魏巍,谭建荣,冯毅雄等.基于改进的非支配排序遗传算法的模块化产品多目标配置优化研究[J].2007,13(11)：2092-2098.
[44]高天一,孙伟,马沁怡.基于粗糙集理论的产品配置规则获取方法研究[J].计算机工程与应用,2007,43(16)：21-21.
[45]Dai Z, Scot T M. Product platform design through sensitivity analysis and cluster analysis [J]. Journal of Intelligent Manufacturing,2007,18(1):97-113.
[46]Kumar R, Allada V. Scalable platforms using ant colony optimization [J]. Journal of Intelligent Manufacturing,2007,18(1):127-142.
[47]Chen Chunbao, Wang Liya. Modified genetic algorithm applied to solve product family optimization problem [J]. Chinese Journal of Mechanical Engineering:English Edition, 2007,10(4):106-111.
[48]Khajavirad A, Michalek J, Simpson T. A decomposed genetic algorithm for solving the joint product family optimization problem [C]//Proceedings of the 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 23-26,2007, Honolulu Hawaii. USA:AIAA, c2007:2111-2124.
[49]李斌,陈立平,钟毅芳.基于多目标遗传算法的产品优化配置研究[J].中国机械工程,2004,15(20)：1819-1822.
[50]轩辕思思,姜兆.产品配置的模糊求解及优化算法研究[J].武汉理工大学学报,2009,31(13)：95-98.
[51]黄辉,梁工谦,隋海燕.大规模定制产品族设计中的原理聚类研究[J].管理工程学报,2008,22(3)：110-114.
[52]李中凯,谭建荣,冯毅雄等.基于混合协同进化算法的可调节产品族优化设计[J].2008,14(8)：1457-1464.
[53]史俊友,陶庆斌,翟红岩.基于遗传算法的产品族模块划分[J].青岛科技大学学报(自然科学版),2010,31(2)：188-193.
[54]丁力平,冯毅雄,谭建荣等.基于性能稳健指数的产品族稳健优化设计[J].2010,16(6)：1121-1130.
[55]姜婷婷,张强,魏小鹏等.基于改进的BPSO算法的产品优化配置求解模型研究[J].计算机应用与软件,2010,27(5)：109-112.
[56]刘勇,丁俊健,张尚先等.基于产品合适度的产品族最优组成模块的确定[J].机械设计,2010,27(4)：29-32.
[57]雒兴刚,蔡莉青,Kwong C K.产品族设计的多目标优化方法[J].计算机集成制造系统,2011,17(7)：1345-1355.
[58]华尔天,肖军军,刘科红.一种基于模糊聚类和粗糙集的产品族设计知识约简方法[J].计算机应用研究,2011,28(11)：4064-4066.
[59]罗好,郭钢.面向客户需求基于灰色粗糙模型的产品配置研究[J].中国机械工程,2012，23(11)：1302-1307.
[60]Mitchell M Tseng, Jian-xin Jiao. A module identification approach to the electrical design of electronic products by clustering analysis of the design matrix [J]. Computers and Industrial Engineering,1997,33(1/2):229-233.
[61]但斌.面向大规模定制的产品族功能性评价与选择方法[J].管理工程学报,2004,18(1)：17-21.
[62]王海军,孙宝元,王吉军等.面向大规模定制的产品模块化设计方法[J].计算机集成制造系统,2004,10(10)：1171-1176.
[63]鲁聪达,吕超群,刘高进等.面向客户需求的产品配置方案模糊综合评价[J].现代制造工程,2006，(10)：17-20.
[64]王忠浩,邵新宇,张国军等.基于粗糙集神经网络的产品族配置性能预测方法[J].机械工程学报,2007,43(5)：85-90.
[65]Ahmed F, Capretz L F, Samarabandu J. Fuzzy inference system for software product family process evaluation[J]. Information Sciences,2008,178(13):2780-2793.
[66]秦红斌.基于公共产品平台的产品族设计技术研究[D].武汉：华中科技大学,2006.
[67]Steven C Wheelwright, Kim B Cliark. Creating project plans to focus product development [J]. Harvard Business Review,1992,70(2):67-83.
[68]谢友柏.现代设计理论和方法的研究[J].机械工程学报,2004,40(4)：1-9.
[69]Suh N P. The principle of design [M]. New York:Oxford University Press,1990:56-85.
[70]Suh N P. Axiomatic design of mechanical systems [J]. The Journal of Mechanical Design and the Journal of Vibration and Acoustics,1995,117(b):2-10.
[71]Huang G Q, Huang J, Mak K L. Agent-based workflow management in collaborative product development on the internet [J]. Computer-Aided Design,2000,32(2):133-144.
[72]Wu Shengli, Sheth A P, Miller J A, et al. Authorization and access control on application data in workflow systems [J]. Journal of Intelligent Information Systems.2002,18(1): 74-88.
[73]Hollings W D. The workflow reference model. WF WOTC-1003, Issuel.1[R], Brussels, Belgium:Workflow Management Coalition,1997.
[74]Fan W H, Ge Z Y, Xiong G L, et al. Study on PDM-based product development process management [J]. High-Tech Letters,2004,10(3):63-68.
[75]Van der Aalst W M P, Ter Hofstede A H M. Verification of workflow task structures: a Petri-net-based approach [J]. Information Systems,2000,25(1):43-69.
[76]Van der Aalst W M P, Ter Hofstede A H M, Kiepuszewski B, et al. Workflow patterns [J]. Distributed and Parallel Databases,2003,14(1):5-51
[77]Sadiq W, Orlovska M E. Analyzing process models using graph reduction techniques [J]. Information Systems,2000,25(2):117-134.
[78]Wil Van Der Aalst. The application of petri nets to workflow management [J]. The Journal of Circuits, Systems and Computers,1998,8(1):21-66.
[79]汪峥,严洪森,刘震玲等.基于ESHLEP-N的产品开发过程建模、调度与仿真[J].控制与决策,2001，6(3)：282-286.
[80]祖旭,黄洪钟,周峰等.产品开发过程资源管理及其仿真[J].系统仿真学报,2005,17(6)：1322-1325.
[81]彭良武,卢睿,刘振.产品设计项目过程管理的研究与实现[J].计算机集成制造系统,2008,14(1)：89-95.
[82]窦万春,蔡士杰.基于Petri网的工作流技术复合建摸与系统分解[J].计算机集成制造系统,2002,8(5)：361-365.
[83]Petri C. A. Fundamentals of a theory of asynchronous information flow [C]. Proceedings of the 1st IFIP World Computer Congress, North Holland,1963:386-390.
[84]Petri C A. Communication with Automata[R]. New York:Griffiss Air Force Base,1966.
[85]袁崇义.Petri网原理与应用[M].北京：电子工业出版社,2005：49-53.
[86]刘峰.基于着色Petri网的工作流建模与分析研究[D].无锡：江南大学,2008.
[87]Salimifard K, Wright M. Petri net-based modeling of workflow systems:an overview [J]. European Journal of Operational Research,2001,134(3):664-676.
[88]曾艳林.基于Petri网的工作流过程建模的研究[D].大连：大连海事大学,2007.
[89]周建涛,史美林,叶新铭.一种基于Petri网化简的工作流过程语义验证方法[J].软件学报,2005，16(1)：1-9.
[90]Wil Van Der Aalst. Loosely coupled interorganizational workflows:modeling and analyzing workflows crossing organizational boundaries [J]. Information & Management, 2000,37(2):67-75.
[91]Hsieh F S. Model and control holonic manufacturing systems based on fusion of contract nets and Petri nets [J]. Automatica,2004,40(1):51-57.
[92]Bezdek J C, Pal N R. Some new indexes of cluster validity [J]. IEEE Transactions on System, Man and Cybernetics,1998,28(Part B):301-315.
[93]Eusuff M M, Lansey K E. Optimization of water distribution network design using the shuffled frog leaping algorithm [J]. Journal of Water Resources Planning and Management, 2003,129(3):210-225.
[94]Kennedy J, Eberhart R. Particle swarm optimization [C]. Proc. IEEE Int. Conf. on Neural Networks. Perth,1995:1942-1948
[95]Elbeltagi E, Hezagy T, Grierson D. Comparison among five evolutionary-based optimization algorithms [J]. Advanced Engineering Informatics,2005,19(1):43-53.
[96]Rahimi-Vahed A, Mirzaei A H. A hybrid multi-objective shuffled frog-leaping algorithm for a mixed-model assembly line sequencing problem [J]. Computers and Industrial Engineering,2007,53(4):642-666.
[97]骆剑平,李霞,陈泯融.混合蛙跳算法的Markov模型及其收敛性分析[J].电子学报,2010,38(12)：2875-2880.
[98]Mashhadi Kashtiban A, Alinia Ahandani M. Various strategies for partitioning of memeplexes in shuffled frog leaping algorithm [C]. Proceedings of the 14th International CSI Computer Conference,2009:576-581.
[99]Huynh Thai-hoang. A modified shuffled frog leaping algorithm for optimal tuning of multivariable PID controller s[C]. IEEE International Conferece on Industrial Technology, Chengdu,2008:1-6.
[100]Zhang Xun-cai, Hu Xue-mei, Cui Guang-zhao, et al. An improved shuffled frog leaping algorithm with cognitive behavior [C]. Proceedings of the 7th WCICA Conference, Chongqing,2008:6197-6202.
[101]郑仕链,楼才义,杨小牛.基于改进混合蛙跳算法的认知无线电协作频谱感知[J].物理学报,2010,59(5)：3611-3617.
[102]Eusuff M, Lansey K, Pasha F. Shuffled frog-leaping algorithm:amemetic meta-heuristic for discrete optimization [J].2006,38(2):129-154.
[103]李英海,周建中,杨俊杰等.一种基于阈值选择策略的改进混合蛙跳算法[J].计算机工程与应用,2007,43(35)：19-21.
[104]赵鹏军,刘三阳.求解复杂函数优化问题的混合蛙跳算法[J].计算机应用研究,2009,26(7)：2435-2437.
[105]Antariksha Bhaduri. A clonal selection based shuffled frog leaping algorithm [C]. IEEE International Advance Computing Conference,2009:125-130.
[106]Li Ying-hai, Dong Xiao-hua, and Liu Ji. Grouping-shuffling particle swarm optimization:an improved PSO for continuous optimization [C]. LNCS,2010,6145: 86-93.
[107]Zhen Zi-yang, Wang Zhi-sheng, Gu Zhou, et al. A novel memetic algorithm for global optimization based on PSO and SFLA [C]. LNCS,2007,4683:127-136.
[108]Gunhui Chung, Lansey K. Application of the shuffled frog leaping algorithm for the optimization of a general large-scale water supply system [J]. Water Resour Manage, 2009,23:797-823.
[109]Elbehairy H, Elbeltagi E, Hegazy T, Soudki K. Comparison of two evolutionary algorithms for optimization of bridge deck repairs [J]. Computer-Aided Civil and Infrastructure Engineering,2006,21 (8):561-572.
[110]骆剑平,李霞,陈泯融.基于改进混合蛙跳算法的CVRP求解[J].电子与信息学报,2011,33(2)：429-434.
[111]Rahimi-Vahed, Dangchi M, Rafiei H. A novel hybrid multi-objective shuffled frog-leaping algorithm for a bi-criteria permutation flow shop scheduling problem [J]. International Journal of Advanced Manufacturing Technology,2009,41(11-12): 1227-1239.
[112]朱光宇.模因内三角概率选择混合蛙跳算法[J].计算机集成制造系统,2009,15(10)：1979-1985.
[113]蔡良伟,李霞.基于混合蛙跳算法的作业车间调度优化[J].深圳大学学报理工版,2010,27(4)：391-395.
[114]王亚敏,冀俊忠,潘全科.基于离散蛙跳算法的零空闲流水线调度问题求解[J].北京工业大学学报,2010,36(1)：124-130.
[115]Pan Q K, Wang L, Gao L, et al. An effective shuffled frog-leaping algorithm for lot-streaming flow shop scheduling problem [J]. International Journal of Advanced Manufacturing Technology,2011,52(5-8):699-713.
[116]罗雪晖,杨烨,李霞.改进混合蛙跳算法求解旅行商问题[J].通信学报,2009,30(7)：130-135.
[117]骆剑平,李霞.求解TSP的改进混合蛙跳算法[J].深圳大学学报理工版,2010,27(2)：173-179.
[118]王亚敏,潘全科,冀俊忠.求解考试时间安排问题的离散蛙跳算法[J].计算机工程与应用,2009,45(36)：40-43.
[119]Yang Cheng-san, Chuang Li-yeh, Ke Chao-Hsuan, Yang Cheng-hong. A combination of shuffled frog-leaping algorithm and genetic algorithm for gene selection [J]. Journal of Advanced Computational Intelligence and Intelligent Informatics,2008,12(3): 218-226.
[120]Duc-Hoang Nguyen, Thai-Hoang Huynh. A SFLA-based fuzzy controller for balancing a ball and beam system [C]. The 10th Intl. Conf. on Control, Automation, Robotics and Vision,2008:1948-1953.
[121]杜长海,黄席樾,杨祖元等.改进的FCM聚类在交通时段自动划分中的应用[J].计算机工程与应用,2009,45(24)：190-193.
[122]Amiri B, Fathian M, Maroosi A. Application of shuffled frog-leaping algorithm on clustering [J]. International Journal of Advanced Manufacturing Technology,2009, 45:199-209.
[123]陈功贵,李智欢,陈金富等.含风电场电力系统动态优化潮流的混合蛙跳算法[J].电力系统自动化,2009,25(4)：25-30.
[124]岳克强,赵知劲,尚俊娜等.智能优化在多用户检测中的应用[J].计算机工程与应用,2009,45(26)：90-93.
[125]Antariksha Bhaduri. Color image segmentation using clonal selection-based shuffled frog leaping algorithm [C]. International Conference on Advances in Recent Technologies in Communication and Computing,2009:517-520.
[126]Wang Zi-qiang, Sun Xia. Image watermarking scheme based on shuffled frog leaping algorithm [C]. IEEE International Symposium on Knowledge Acquisition and Modeling Workshop,2008:239-242.
[127]Dunn J C. A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters [J]. Journal Cybern,1973,3(3):32-57.
[128]Halkidi M, Batistakis Y, Vazirgiannis M. On clustering validation techniques [J]. JIIS,2001,17(2-3):107-145.
[129]Shelokar P S, Jayaraman V K, Kulkarni B D. An ant colony approach for clustering [J]. Analytica Chimica Acta,2004,509 (2):187-195.
[130]刘文远,王颖洁,邓成玉等.基于遗传算法的模糊聚类分析[J].计算机工程,2004,30(19)：117-118.
[131]Xie X L, Beni G. A validity measure for fuzzy clustering [J]. IEEE Trans. On Pattern Analysis and Machine Intelligence,1991,13(8):841-847.
[132]Fukuyama Y, Sugeno M. A new method of choosing the number of clusters for the fuzzy c-means method [C]. Proc.5th Fuzzy Syst. Symp., Japan,1989:247-250.
[133]Kwon S H. Cluster validity index for fuzzy clustering [J]. Electron. Lett,1998,34(22): 2176-2177.
[134]Chen M Y, Linkens D A. Rule-base self-generation and simplification for data-driven fuzzy models [J]. Fuzzy Sets and Systems,2004,142(2):243-265.
[135]Yu Jian, Cheng Qian-sheng, The search scope of optimal cluster number in fuzzy clustering methods [J]. Science in China (Series E),2002,32(4),274-280.
[136]Wang Jie-sheng, Gao Xian-wen. Optimization of Fuzzy C-Means Clustering by Genetic Algorithms Based on Sizable Chromosome [C]. Chinese Conference on Pattern Recognition. China,2009:1-5.
[137]Pal N R, Bezdek J C. On cluster validity for the fuzzy c-means model [J]. IEEE Trans. Fuzzy Systems,1995,3(3):370-379.
[138]Hegge H M H, Wortmann J C. Generic Bill of material:a new product model [J]. International Journal of Production Economics,1991,23:117-128.
[139]Vapnik V N. The Nature of Statistical Learning Theory [M]. NY:Springer-Verlag,1995: 67-72.
[140]崔文华,刘晓冰,王伟等.混合蛙跳算法研究综述[J].控制与决策,2012,27(4)：481-486.
[141]Guo J Q, Zheng L. A modified simulated annealing algorithm for estimating solute transport parameters in streams from tracer experiment data [J]. Environmental Modeling and Software,2005,20(6),811-815.
[142]Joe Peppard. Customer Relationship Management (CRM) in Financial Services[J]. European Management Journal,2000,18(3):312-327.
[143]Samuel Robert Collins, Sharkant Navathe. XML schema mappings for heterogeneous database access [J]. Information and Software Technology,2002,44(4):251-257.
[144]Shyh-KweiChen, Ming LingLo, Kun-LungWu. A practical approach to extracting DTD-conforming XML documents from heterogeneous data sources [J]. Information Sciences,2006,176(6):820-844.
[2]王爱民,肖天元,孟明辰.面向大规模定制的配置设计技术研究[J].计算机集成制造系统,2004,10(11)：1326-1337.
[3]Simpson T W, Maier J R A, Mistree F. Product platform design:method and application [J]. Research in Engineering Design,2001,13(1):2-22.
[4]Jiao J X, Tseng M M, Vincent G. Duffy, Fuhua Lin. Product family modeling for mass customization[J]. Computers & Industrial Engineering,1998,35(3-4):495-498.
[5]Tseng M M, Jiao J X. A variant approach to product definition by recognizing functional requirement patterns [J]. Journal of Engineering Design,1997,8(4):329-340.
[6]Bimal Nepal, Leslie Monplaisir, Oluwafemi Famuyiwa. Matching product architecture with supply chain design [J]. European Journal of Operational Research,2012,216(2): 312-325.
[7]Egon Ostrosi, Alain-Jerome Fougeres, Michel Ferney. Fuzzy agents for product configuration in collaborative and distributed design process [J]. Applied Soft Computing,2012,12(8):2091-2105.
[8]Carlos Alberto Costa, Marcos Alexandre Luciano, Celson Pantoja Lima, Robert I. M. Young. Assessment of a product range model concept to support design reuse using rule based systems and case based reasoning [J]. Advanced Engineering Informatics,2012,26(2): 292-305.
[9]Adam L Chen, Daniel H Martinez. A heuristic method based on genetic algorithm for the baseline-product design [J]. Expert Systems with Applications,2012,39(5): 5829-5837.
[10]E Francalanza, J C Borg, C L Constantinescu. A Case for Assisting'Product Family' Manufacturing System Designers [J]. Procedia CIRP,2012,3:376-381.
[11]Yaser Ghanam, Frank Maurer, Pekka Abrahamsson. Making the leap to a software platform strategy:Issues and challenges [J]. Information and Software Technology,2012,54(9): 968-984.
[12]D Xue, G Hua, V Mehrad, P Gu. Optimal adaptable design for creating the changeable product based on changeable requirements considering the whole product life-cycle [J]. Journal of Manufacturing Systems,2012,31 (1):59-68.
[13]Jiao J, Simpson T W, Siddique Z. Product family design and platform-based product development:a state-of-theart review [J]. Journal of Intelligent Manufacturing,2007, 18(1):5-29.
[14]Dong Yang, Ming Dong. A constraint satisfaction approach to resolving product configuration conflicts [J]. Advanced Engineering Informatics,2012,26(3):592-602.
[15]H Panetto, M Dassisti, A Tursi. ONTO-PDM:Product-driven ONTOlogy for Product Data Management interoperability within manufacturing process environment [J]. Advanced Engineering Informatics,2012,26(2):334-348.
[16]Thevenot H J, Simpson T W. Commonality indices for product family design:a detailed Comparison [J]. Journal of Engineering Design,2006,17(2):99-119.
[17]刘晓冰,董建华,孙伟.面向产品族的建模技术研究[J].计算机辅助设计与图形学学报,2001,13(7)：636-641.
[18]王爱民,孟明辰,黄靖远.面向产品族规划的核心平台数学描述及确定方法[J].清华大学学报(自然科学版),2002,42(8)：1049-1052.
[19]李占山,寇飞宏,欧阳丹彤.产品配置器的研究进展[J].吉林大学学报(自然科学版),2006,44(3)：429-438.
[20]Zheng L Y, Dong H F, Vichare P, et al. Systematic modeling and reusing of process knowledge for rapid process configuration [J]. Robotics and Computer-Integrated Manufacturing,2008,24(6):763-772.
[21]叶世琴,但斌.大规模定制产品族模块定制属性分析模型[J].工业工程,2007,10(6)：72-75.
[22]Michael D. Johnson, Randolph E. Kirchain. Quantifying the effects of product family decisions on material selection:A process-based costing approach[J]. International Journal of Production Economics,2009,120(2):653-668.
[23]赵燕伟,苏楠,张峰等.基于可拓实例推理的产品族配置设计方法[J].机械工程学报,2010,46(15)：146-154.
[24]伊辉勇,刘伟.基于顾客满意度的在线定制产品族规模优化[J].工业工程与管理,2011,16(6)：55-59.
[25]Messac A, Martinez M, Simpson T. Effective product family design using physical programming [J]. Engineering Optimization,2002,34(3):245-261.
[26]Messac A, Martinez M, Simpson T. Introduction of a product family penalty function using physical programming [J]. Journal of Mechanical Design,2002,124(2):164-172.
[27]Jacques Lamothe, Khaled Hadj-Hamou, Michel Aldanondo. An optimization model for selecting a product family and designing its supply chain[J]. European Journal of Operational Research,2006,169(3):1030-1047.
[28]高卫国,徐燕申,陈永亮等.广义模块化设计原理及方法[J].机械工程学报,2007,43(6)：48-54.
[29]Galan R, Racero J, Eguia I, Garcia J M. A systematic approach for product families formation in Reconfigurable Manufacturing Systems[J]. Robotics and Computer-Integrated Manufacturing,2007,23(5):489-502.
[30]万雪峰,但斌,经有国.在线大规模定制下基于客户需求模板的产品配置研究[J].工业工程,2010,13(4)：69-73.
[31]Elmaraghy H, Azab A, Schuh G, et al. Managing variations in products, processes and manufacturing systems [J]. CIRP Annals-Manufacturing Technology,2009,58(1): 441-446.
[32]郑联语,纪录.产品族工装配置技术研究与实现[J].计算机集成制造系统,2011,17(3)：585-594.
[33]雒兴刚,杨勇.基于联合分析的可配置产品优化选择方法[J].中国机械工程,2012,23(5)：578-584.
[34]侯亮,唐任仲,徐燕申.产品模块化设计理论、技术与应用研究进展[J].机械工程学报,2004,40(1)：56-61.
[35]张换高,赵文燕,江屏等.基于相似性与结构敏感性分析的产品平台设计过程模型[J].机械工程学报,2012,48(11)：104-118.
[36]Timothy Simpson, Bryan D'Souza. Assessing variable levels of platform commonality within a product family using a multiobjective genetic algorithm [C]//Proceedings of the 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, September 4-6,2002, Atlanta, Georgia. USA:AIAA, c2002:1-17.
[37]张利.大批量定制模型的客户驱动参数映射与描述结构研究[J].合肥工业大学学报(自然科学版),2003,26(6)：1152-1156.
[38]秦红斌,肖人彬,陈义保等.面向公共产品平台通用化的聚类分析方法研究[J].计算机辅助设计与图形学学报,2004,16(4)：518-522.
[39]Wheelwright Steven C, Clark Kim B. Creating project plans to focus product development [J]. Harvard Business Review,1992,70(2):67-83.
[40]王爱民,肖田元,范莉娅等.面向产品族的制造单元聚类规划研究[J].计算机集成制造系统,2004,10(10)：1257-1261.
[41]王爱民,肖田元,赵银燕等.面向产品族模块化设计和制造的工艺聚类分析方法[J].清华大学学报(自然科学版),2004,44(10)：1394-1397.
[42]孙国梓,郁鼎文,吴志军.个性化配置器的粗糙集方法研究[J].计算机集成制造系统,2005,11(2)：168-172.
[43]魏巍,谭建荣,冯毅雄等.基于改进的非支配排序遗传算法的模块化产品多目标配置优化研究[J].2007,13(11)：2092-2098.
[44]高天一,孙伟,马沁怡.基于粗糙集理论的产品配置规则获取方法研究[J].计算机工程与应用,2007,43(16)：21-21.
[45]Dai Z, Scot T M. Product platform design through sensitivity analysis and cluster analysis [J]. Journal of Intelligent Manufacturing,2007,18(1):97-113.
[46]Kumar R, Allada V. Scalable platforms using ant colony optimization [J]. Journal of Intelligent Manufacturing,2007,18(1):127-142.
[47]Chen Chunbao, Wang Liya. Modified genetic algorithm applied to solve product family optimization problem [J]. Chinese Journal of Mechanical Engineering:English Edition, 2007,10(4):106-111.
[48]Khajavirad A, Michalek J, Simpson T. A decomposed genetic algorithm for solving the joint product family optimization problem [C]//Proceedings of the 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 23-26,2007, Honolulu Hawaii. USA:AIAA, c2007:2111-2124.
[49]李斌,陈立平,钟毅芳.基于多目标遗传算法的产品优化配置研究[J].中国机械工程,2004,15(20)：1819-1822.
[50]轩辕思思,姜兆.产品配置的模糊求解及优化算法研究[J].武汉理工大学学报,2009,31(13)：95-98.
[51]黄辉,梁工谦,隋海燕.大规模定制产品族设计中的原理聚类研究[J].管理工程学报,2008,22(3)：110-114.
[52]李中凯,谭建荣,冯毅雄等.基于混合协同进化算法的可调节产品族优化设计[J].2008,14(8)：1457-1464.
[53]史俊友,陶庆斌,翟红岩.基于遗传算法的产品族模块划分[J].青岛科技大学学报(自然科学版),2010,31(2)：188-193.
[54]丁力平,冯毅雄,谭建荣等.基于性能稳健指数的产品族稳健优化设计[J].2010,16(6)：1121-1130.
[55]姜婷婷,张强,魏小鹏等.基于改进的BPSO算法的产品优化配置求解模型研究[J].计算机应用与软件,2010,27(5)：109-112.
[56]刘勇,丁俊健,张尚先等.基于产品合适度的产品族最优组成模块的确定[J].机械设计,2010,27(4)：29-32.
[57]雒兴刚,蔡莉青,Kwong C K.产品族设计的多目标优化方法[J].计算机集成制造系统,2011,17(7)：1345-1355.
[58]华尔天,肖军军,刘科红.一种基于模糊聚类和粗糙集的产品族设计知识约简方法[J].计算机应用研究,2011,28(11)：4064-4066.
[59]罗好,郭钢.面向客户需求基于灰色粗糙模型的产品配置研究[J].中国机械工程,2012，23(11)：1302-1307.
[60]Mitchell M Tseng, Jian-xin Jiao. A module identification approach to the electrical design of electronic products by clustering analysis of the design matrix [J]. Computers and Industrial Engineering,1997,33(1/2):229-233.
[61]但斌.面向大规模定制的产品族功能性评价与选择方法[J].管理工程学报,2004,18(1)：17-21.
[62]王海军,孙宝元,王吉军等.面向大规模定制的产品模块化设计方法[J].计算机集成制造系统,2004,10(10)：1171-1176.
[63]鲁聪达,吕超群,刘高进等.面向客户需求的产品配置方案模糊综合评价[J].现代制造工程,2006，(10)：17-20.
[64]王忠浩,邵新宇,张国军等.基于粗糙集神经网络的产品族配置性能预测方法[J].机械工程学报,2007,43(5)：85-90.
[65]Ahmed F, Capretz L F, Samarabandu J. Fuzzy inference system for software product family process evaluation[J]. Information Sciences,2008,178(13):2780-2793.
[66]秦红斌.基于公共产品平台的产品族设计技术研究[D].武汉：华中科技大学,2006.
[67]Steven C Wheelwright, Kim B Cliark. Creating project plans to focus product development [J]. Harvard Business Review,1992,70(2):67-83.
[68]谢友柏.现代设计理论和方法的研究[J].机械工程学报,2004,40(4)：1-9.
[69]Suh N P. The principle of design [M]. New York:Oxford University Press,1990:56-85.
[70]Suh N P. Axiomatic design of mechanical systems [J]. The Journal of Mechanical Design and the Journal of Vibration and Acoustics,1995,117(b):2-10.
[71]Huang G Q, Huang J, Mak K L. Agent-based workflow management in collaborative product development on the internet [J]. Computer-Aided Design,2000,32(2):133-144.
[72]Wu Shengli, Sheth A P, Miller J A, et al. Authorization and access control on application data in workflow systems [J]. Journal of Intelligent Information Systems.2002,18(1): 74-88.
[73]Hollings W D. The workflow reference model. WF WOTC-1003, Issuel.1[R], Brussels, Belgium:Workflow Management Coalition,1997.
[74]Fan W H, Ge Z Y, Xiong G L, et al. Study on PDM-based product development process management [J]. High-Tech Letters,2004,10(3):63-68.
[75]Van der Aalst W M P, Ter Hofstede A H M. Verification of workflow task structures: a Petri-net-based approach [J]. Information Systems,2000,25(1):43-69.
[76]Van der Aalst W M P, Ter Hofstede A H M, Kiepuszewski B, et al. Workflow patterns [J]. Distributed and Parallel Databases,2003,14(1):5-51
[77]Sadiq W, Orlovska M E. Analyzing process models using graph reduction techniques [J]. Information Systems,2000,25(2):117-134.
[78]Wil Van Der Aalst. The application of petri nets to workflow management [J]. The Journal of Circuits, Systems and Computers,1998,8(1):21-66.
[79]汪峥,严洪森,刘震玲等.基于ESHLEP-N的产品开发过程建模、调度与仿真[J].控制与决策,2001，6(3)：282-286.
[80]祖旭,黄洪钟,周峰等.产品开发过程资源管理及其仿真[J].系统仿真学报,2005,17(6)：1322-1325.
[81]彭良武,卢睿,刘振.产品设计项目过程管理的研究与实现[J].计算机集成制造系统,2008,14(1)：89-95.
[82]窦万春,蔡士杰.基于Petri网的工作流技术复合建摸与系统分解[J].计算机集成制造系统,2002,8(5)：361-365.
[83]Petri C. A. Fundamentals of a theory of asynchronous information flow [C]. Proceedings of the 1st IFIP World Computer Congress, North Holland,1963:386-390.
[84]Petri C A. Communication with Automata[R]. New York:Griffiss Air Force Base,1966.
[85]袁崇义.Petri网原理与应用[M].北京：电子工业出版社,2005：49-53.
[86]刘峰.基于着色Petri网的工作流建模与分析研究[D].无锡：江南大学,2008.
[87]Salimifard K, Wright M. Petri net-based modeling of workflow systems:an overview [J]. European Journal of Operational Research,2001,134(3):664-676.
[88]曾艳林.基于Petri网的工作流过程建模的研究[D].大连：大连海事大学,2007.
[89]周建涛,史美林,叶新铭.一种基于Petri网化简的工作流过程语义验证方法[J].软件学报,2005，16(1)：1-9.
[90]Wil Van Der Aalst. Loosely coupled interorganizational workflows:modeling and analyzing workflows crossing organizational boundaries [J]. Information & Management, 2000,37(2):67-75.
[91]Hsieh F S. Model and control holonic manufacturing systems based on fusion of contract nets and Petri nets [J]. Automatica,2004,40(1):51-57.
[92]Bezdek J C, Pal N R. Some new indexes of cluster validity [J]. IEEE Transactions on System, Man and Cybernetics,1998,28(Part B):301-315.
[93]Eusuff M M, Lansey K E. Optimization of water distribution network design using the shuffled frog leaping algorithm [J]. Journal of Water Resources Planning and Management, 2003,129(3):210-225.
[94]Kennedy J, Eberhart R. Particle swarm optimization [C]. Proc. IEEE Int. Conf. on Neural Networks. Perth,1995:1942-1948
[95]Elbeltagi E, Hezagy T, Grierson D. Comparison among five evolutionary-based optimization algorithms [J]. Advanced Engineering Informatics,2005,19(1):43-53.
[96]Rahimi-Vahed A, Mirzaei A H. A hybrid multi-objective shuffled frog-leaping algorithm for a mixed-model assembly line sequencing problem [J]. Computers and Industrial Engineering,2007,53(4):642-666.
[97]骆剑平,李霞,陈泯融.混合蛙跳算法的Markov模型及其收敛性分析[J].电子学报,2010,38(12)：2875-2880.
[98]Mashhadi Kashtiban A, Alinia Ahandani M. Various strategies for partitioning of memeplexes in shuffled frog leaping algorithm [C]. Proceedings of the 14th International CSI Computer Conference,2009:576-581.
[99]Huynh Thai-hoang. A modified shuffled frog leaping algorithm for optimal tuning of multivariable PID controller s[C]. IEEE International Conferece on Industrial Technology, Chengdu,2008:1-6.
[100]Zhang Xun-cai, Hu Xue-mei, Cui Guang-zhao, et al. An improved shuffled frog leaping algorithm with cognitive behavior [C]. Proceedings of the 7th WCICA Conference, Chongqing,2008:6197-6202.
[101]郑仕链,楼才义,杨小牛.基于改进混合蛙跳算法的认知无线电协作频谱感知[J].物理学报,2010,59(5)：3611-3617.
[102]Eusuff M, Lansey K, Pasha F. Shuffled frog-leaping algorithm:amemetic meta-heuristic for discrete optimization [J].2006,38(2):129-154.
[103]李英海,周建中,杨俊杰等.一种基于阈值选择策略的改进混合蛙跳算法[J].计算机工程与应用,2007,43(35)：19-21.
[104]赵鹏军,刘三阳.求解复杂函数优化问题的混合蛙跳算法[J].计算机应用研究,2009,26(7)：2435-2437.
[105]Antariksha Bhaduri. A clonal selection based shuffled frog leaping algorithm [C]. IEEE International Advance Computing Conference,2009:125-130.
[106]Li Ying-hai, Dong Xiao-hua, and Liu Ji. Grouping-shuffling particle swarm optimization:an improved PSO for continuous optimization [C]. LNCS,2010,6145: 86-93.
[107]Zhen Zi-yang, Wang Zhi-sheng, Gu Zhou, et al. A novel memetic algorithm for global optimization based on PSO and SFLA [C]. LNCS,2007,4683:127-136.
[108]Gunhui Chung, Lansey K. Application of the shuffled frog leaping algorithm for the optimization of a general large-scale water supply system [J]. Water Resour Manage, 2009,23:797-823.
[109]Elbehairy H, Elbeltagi E, Hegazy T, Soudki K. Comparison of two evolutionary algorithms for optimization of bridge deck repairs [J]. Computer-Aided Civil and Infrastructure Engineering,2006,21 (8):561-572.
[110]骆剑平,李霞,陈泯融.基于改进混合蛙跳算法的CVRP求解[J].电子与信息学报,2011,33(2)：429-434.
[111]Rahimi-Vahed, Dangchi M, Rafiei H. A novel hybrid multi-objective shuffled frog-leaping algorithm for a bi-criteria permutation flow shop scheduling problem [J]. International Journal of Advanced Manufacturing Technology,2009,41(11-12): 1227-1239.
[112]朱光宇.模因内三角概率选择混合蛙跳算法[J].计算机集成制造系统,2009,15(10)：1979-1985.
[113]蔡良伟,李霞.基于混合蛙跳算法的作业车间调度优化[J].深圳大学学报理工版,2010,27(4)：391-395.
[114]王亚敏,冀俊忠,潘全科.基于离散蛙跳算法的零空闲流水线调度问题求解[J].北京工业大学学报,2010,36(1)：124-130.
[115]Pan Q K, Wang L, Gao L, et al. An effective shuffled frog-leaping algorithm for lot-streaming flow shop scheduling problem [J]. International Journal of Advanced Manufacturing Technology,2011,52(5-8):699-713.
[116]罗雪晖,杨烨,李霞.改进混合蛙跳算法求解旅行商问题[J].通信学报,2009,30(7)：130-135.
[117]骆剑平,李霞.求解TSP的改进混合蛙跳算法[J].深圳大学学报理工版,2010,27(2)：173-179.
[118]王亚敏,潘全科,冀俊忠.求解考试时间安排问题的离散蛙跳算法[J].计算机工程与应用,2009,45(36)：40-43.
[119]Yang Cheng-san, Chuang Li-yeh, Ke Chao-Hsuan, Yang Cheng-hong. A combination of shuffled frog-leaping algorithm and genetic algorithm for gene selection [J]. Journal of Advanced Computational Intelligence and Intelligent Informatics,2008,12(3): 218-226.
[120]Duc-Hoang Nguyen, Thai-Hoang Huynh. A SFLA-based fuzzy controller for balancing a ball and beam system [C]. The 10th Intl. Conf. on Control, Automation, Robotics and Vision,2008:1948-1953.
[121]杜长海,黄席樾,杨祖元等.改进的FCM聚类在交通时段自动划分中的应用[J].计算机工程与应用,2009,45(24)：190-193.
[122]Amiri B, Fathian M, Maroosi A. Application of shuffled frog-leaping algorithm on clustering [J]. International Journal of Advanced Manufacturing Technology,2009, 45:199-209.
[123]陈功贵,李智欢,陈金富等.含风电场电力系统动态优化潮流的混合蛙跳算法[J].电力系统自动化,2009,25(4)：25-30.
[124]岳克强,赵知劲,尚俊娜等.智能优化在多用户检测中的应用[J].计算机工程与应用,2009,45(26)：90-93.
[125]Antariksha Bhaduri. Color image segmentation using clonal selection-based shuffled frog leaping algorithm [C]. International Conference on Advances in Recent Technologies in Communication and Computing,2009:517-520.
[126]Wang Zi-qiang, Sun Xia. Image watermarking scheme based on shuffled frog leaping algorithm [C]. IEEE International Symposium on Knowledge Acquisition and Modeling Workshop,2008:239-242.
[127]Dunn J C. A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters [J]. Journal Cybern,1973,3(3):32-57.
[128]Halkidi M, Batistakis Y, Vazirgiannis M. On clustering validation techniques [J]. JIIS,2001,17(2-3):107-145.
[129]Shelokar P S, Jayaraman V K, Kulkarni B D. An ant colony approach for clustering [J]. Analytica Chimica Acta,2004,509 (2):187-195.
[130]刘文远,王颖洁,邓成玉等.基于遗传算法的模糊聚类分析[J].计算机工程,2004,30(19)：117-118.
[131]Xie X L, Beni G. A validity measure for fuzzy clustering [J]. IEEE Trans. On Pattern Analysis and Machine Intelligence,1991,13(8):841-847.
[132]Fukuyama Y, Sugeno M. A new method of choosing the number of clusters for the fuzzy c-means method [C]. Proc.5th Fuzzy Syst. Symp., Japan,1989:247-250.
[133]Kwon S H. Cluster validity index for fuzzy clustering [J]. Electron. Lett,1998,34(22): 2176-2177.
[134]Chen M Y, Linkens D A. Rule-base self-generation and simplification for data-driven fuzzy models [J]. Fuzzy Sets and Systems,2004,142(2):243-265.
[135]Yu Jian, Cheng Qian-sheng, The search scope of optimal cluster number in fuzzy clustering methods [J]. Science in China (Series E),2002,32(4),274-280.
[136]Wang Jie-sheng, Gao Xian-wen. Optimization of Fuzzy C-Means Clustering by Genetic Algorithms Based on Sizable Chromosome [C]. Chinese Conference on Pattern Recognition. China,2009:1-5.
[137]Pal N R, Bezdek J C. On cluster validity for the fuzzy c-means model [J]. IEEE Trans. Fuzzy Systems,1995,3(3):370-379.
[138]Hegge H M H, Wortmann J C. Generic Bill of material:a new product model [J]. International Journal of Production Economics,1991,23:117-128.
[139]Vapnik V N. The Nature of Statistical Learning Theory [M]. NY:Springer-Verlag,1995: 67-72.
[140]崔文华,刘晓冰,王伟等.混合蛙跳算法研究综述[J].控制与决策,2012,27(4)：481-486.
[141]Guo J Q, Zheng L. A modified simulated annealing algorithm for estimating solute transport parameters in streams from tracer experiment data [J]. Environmental Modeling and Software,2005,20(6),811-815.
[142]Joe Peppard. Customer Relationship Management (CRM) in Financial Services[J]. European Management Journal,2000,18(3):312-327.
[143]Samuel Robert Collins, Sharkant Navathe. XML schema mappings for heterogeneous database access [J]. Information and Software Technology,2002,44(4):251-257.
[144]Shyh-KweiChen, Ming LingLo, Kun-LungWu. A practical approach to extracting DTD-conforming XML documents from heterogeneous data sources [J]. Information Sciences,2006,176(6):820-844.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |