基于Internet的机械方案优化与评价决策方法研究及系统开发
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摘要
本文的研究工作是国家自然科学基金重点资助项目(50465001)“面向设计与制造过程集成的公差设计模型和方法”的一部分,是山东省科技厅重大基金资助项目(2004GG1104017)“胶东半岛制造业基地信息技术服务平台”的重要组成部分。旨在总结国内外理论成果的基础上,对机械优化设计中的组合优化、基于Vague集及灰色理论的机械方案评价决策方法等方面进行研究,并开发出基于Internet的机械设计方案优化与评价决策系统。
组合优化问题一直是机械优化设计中的难点,而蚁群系统是近年来发展起来的解决组合优化问题的一种新方法,本文利用增强型蚁群系统开发了基于Internet的机械设计方案智能优化系统。通过该系统,可较好地解决方案组合优化设计问题。
在机械设计过程中,常常出现许多种方案,每个方案各有自己的优点,有自己的不足,使得机械运动方案的优劣难以比较,因此需要评价与决策。本文针对目前的模糊评价方法存在的不足提出了基于Vague集及灰色理论的机械方案评价决策方法。本文首先介绍了Vague集(值)的概念,接着分析了现有的几种Vague集(值)之间相似度量的方法。用实例说明这些方法在某些情况下不适用。本文根据造成不适用的原因改进了Vague值相似度量方法并将其应用在机械方案决策中。针对传统模糊综合评判方法的缺陷,本文给出了利用Vague集及灰理论中的区间灰数对机械设计方案进行评价的方法;将灰色系统理论引入方案的多指标模糊决策,形成了基于Vague集的灰色机械设计方案决策模型。并给出实例验证了该方法的有效性。
针对传统的综合评价系统的弊端,本文给出了一种基于Internet的机械方案优化及综合评价的框架模型,明确了系统中各部件的功能及其相互关系,并详细介绍了系统实施的具体过程。本系统主要包括方案优化模块、方案评价与决策模块和优化设计等模块。由于其所有操作逻辑和事务逻辑由各层服务器完成,大大提高了系统的安全性、稳定性、可维护性和可扩展性;并可降低网络负载、提高与用户的交互能力,客户终端只要安装Web浏览器就能使用。其不但可以提高综合评价的开放性和智能性,而且可以使机械方案优化及综合评价在实际中的运用更加灵活,高效。最后通过工程实例分析,验证了其适用性和有效性。
This thesis is supported financially by a key project of the National Science Foundation of China, (Grant No. 50465001) and a key project of the science and technology office of Shandong province, (Grant No.2004GG1104017).By referring and summarizing the latest national and international achievements, the combination optimization of mechanical optimization and the mechanical scheme appraise decision method based on the Vague Set and Grey Theory are researched. Mechanical design scheme optimization and appraisal decision-making system based on Internet are developed.
Combinational optimization problems are always the difficulty in mechanical optimal design. Ant Colony System is a new type method, which is proposed recently to solve some combinational optimization problems. By using Enhanced Ant Colony System, mechanical design scheme intelligence optimization system based on Internet is developed. Scheme combinational optimization problems are solved effectively by using this system.
The projects are manifold sometimes in engineering. Each scheme has its advantage and disadvantage. So it is difficult to compare the excellence with the inferior for mechanical kinematics scheme and it is necessary to evaluate and make decision. Firstly, the concepts of vague sets and vague values are introduced. Then some existing similarity measures are reviewed and compared. It is pointed out that those methods are not always suitable for some cases, and the reasons are analyzed as well. Base on them the similarity measures between vague values and between weighted elements are improved. And it is applied on Mechanical scheme design. In view of the shortcomings of traditional fuzzy unified evaluating method, this thesis proposes a Decision-making Method of the Design Scheme of the Mechanical Based on Vague Set and interval gray number. The multi-attribute fuzzy decision, by introducing gray system theory into the scheme, forms a fuzzy decision-making model based on gray relational analysis. An Example showed the effectiveness of the method.
In view of the shortcomings of traditional comprehensive evaluation decision system, this paper gives the structural framework of Optimization Design of Machinery and comprehensive evaluation decision system based on the Internet, expounds the functions of all components in this system and their mutual relationships, and introduces in detail the concrete procedures of implementing this system. This system is mainly consisted of optimization module, evaluation and decision-making module, optimization design module and so on. All of the operations logic and affairs logic are completed by each layer servers, which greatly improves the security, stability, maintainability and expansibility of the system; and also reduces the load of network, enhances the mutual ability with users. It can work just with Web browser in client terminal. The system cannot only improve the opening and intelligence of the comprehensive evaluation, but also could make mechanical optimization design &comprehensive evaluation agile and effective in practical use. It is demonstrated that the test is practicable and effective by the analysis of an example.
组合优化问题一直是机械优化设计中的难点,而蚁群系统是近年来发展起来的解决组合优化问题的一种新方法,本文利用增强型蚁群系统开发了基于Internet的机械设计方案智能优化系统。通过该系统,可较好地解决方案组合优化设计问题。
在机械设计过程中,常常出现许多种方案,每个方案各有自己的优点,有自己的不足,使得机械运动方案的优劣难以比较,因此需要评价与决策。本文针对目前的模糊评价方法存在的不足提出了基于Vague集及灰色理论的机械方案评价决策方法。本文首先介绍了Vague集(值)的概念,接着分析了现有的几种Vague集(值)之间相似度量的方法。用实例说明这些方法在某些情况下不适用。本文根据造成不适用的原因改进了Vague值相似度量方法并将其应用在机械方案决策中。针对传统模糊综合评判方法的缺陷,本文给出了利用Vague集及灰理论中的区间灰数对机械设计方案进行评价的方法;将灰色系统理论引入方案的多指标模糊决策,形成了基于Vague集的灰色机械设计方案决策模型。并给出实例验证了该方法的有效性。
针对传统的综合评价系统的弊端,本文给出了一种基于Internet的机械方案优化及综合评价的框架模型,明确了系统中各部件的功能及其相互关系,并详细介绍了系统实施的具体过程。本系统主要包括方案优化模块、方案评价与决策模块和优化设计等模块。由于其所有操作逻辑和事务逻辑由各层服务器完成,大大提高了系统的安全性、稳定性、可维护性和可扩展性;并可降低网络负载、提高与用户的交互能力,客户终端只要安装Web浏览器就能使用。其不但可以提高综合评价的开放性和智能性,而且可以使机械方案优化及综合评价在实际中的运用更加灵活,高效。最后通过工程实例分析,验证了其适用性和有效性。
This thesis is supported financially by a key project of the National Science Foundation of China, (Grant No. 50465001) and a key project of the science and technology office of Shandong province, (Grant No.2004GG1104017).By referring and summarizing the latest national and international achievements, the combination optimization of mechanical optimization and the mechanical scheme appraise decision method based on the Vague Set and Grey Theory are researched. Mechanical design scheme optimization and appraisal decision-making system based on Internet are developed.
Combinational optimization problems are always the difficulty in mechanical optimal design. Ant Colony System is a new type method, which is proposed recently to solve some combinational optimization problems. By using Enhanced Ant Colony System, mechanical design scheme intelligence optimization system based on Internet is developed. Scheme combinational optimization problems are solved effectively by using this system.
The projects are manifold sometimes in engineering. Each scheme has its advantage and disadvantage. So it is difficult to compare the excellence with the inferior for mechanical kinematics scheme and it is necessary to evaluate and make decision. Firstly, the concepts of vague sets and vague values are introduced. Then some existing similarity measures are reviewed and compared. It is pointed out that those methods are not always suitable for some cases, and the reasons are analyzed as well. Base on them the similarity measures between vague values and between weighted elements are improved. And it is applied on Mechanical scheme design. In view of the shortcomings of traditional fuzzy unified evaluating method, this thesis proposes a Decision-making Method of the Design Scheme of the Mechanical Based on Vague Set and interval gray number. The multi-attribute fuzzy decision, by introducing gray system theory into the scheme, forms a fuzzy decision-making model based on gray relational analysis. An Example showed the effectiveness of the method.
In view of the shortcomings of traditional comprehensive evaluation decision system, this paper gives the structural framework of Optimization Design of Machinery and comprehensive evaluation decision system based on the Internet, expounds the functions of all components in this system and their mutual relationships, and introduces in detail the concrete procedures of implementing this system. This system is mainly consisted of optimization module, evaluation and decision-making module, optimization design module and so on. All of the operations logic and affairs logic are completed by each layer servers, which greatly improves the security, stability, maintainability and expansibility of the system; and also reduces the load of network, enhances the mutual ability with users. It can work just with Web browser in client terminal. The system cannot only improve the opening and intelligence of the comprehensive evaluation, but also could make mechanical optimization design &comprehensive evaluation agile and effective in practical use. It is demonstrated that the test is practicable and effective by the analysis of an example.
引文
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[3] Adil Baykasoglu, Nabil N.Z. Gindy. A simulated annealing algorithm for dynamic layout problem[J]. Computers & Operations Research, 2001, 28:1403~1426
[4] Chuangyin Dang, Liping He and Ip Kee Hui. A deterministic annealing algorithm for approximating a solution of the max-bisection problem[J]. Neyral Networks, 2002,15:441~458
[5] A. Vince. A framework for the greedy algorithm[J]. Discrete Applied Mathematics,2002, 121:247~260
[6] Ko-Hsin Liang, Xin Yao and Charles Newton, et al. A new evolutionary approach to cuttingstock problems with and without contiguity, Computers & Operations Research[J], 2002, 29:1641~1659
[7] Andrzej Jaszkiewiez. Genetic local search for multi-objective combinatorial optimization[J]. Discrete Optimization, 2002,137:50~71
[8] 王宇平, 徐晨. 解组合优化的一种新方法的收敛性[J]. 西安电子科技大学学报, 1997, 24(4):531~534
[9] Marco Dorigo,Vittorio Maniezzo and Alberto Colorni . The Ant System: Optimization by a colony of cooperating agents[J]. IEEE Transactions on Systems, Man, and Cybernetics–Part B, 1996,26(1):1~13
[10] Walter J. Gutjahr . A Graph-based Ant System and its convergence[J]. Future Generation Computer Systems, 2000, 16 : 873~888
[11] V.K. Jayaraman, B.D. Kulkarni and Sachin Karale, et al . Ant colony framework for optimal design and scheduling of batch plants[J]. Computers and Chemical Engineering , 2000,24: 1901~1912
[12] Luis M. de Campos, Juan M. Fernandez-Luna and Jose A. Gamez, et al. Ant colony optimization for learning Bayesian networks[J]. Intenational Journal of Approximate Reasoning, 2002,31:291~311
[13] 刘占伟,邓四二,月拳弘芍.复杂工程系统设计方案评价方法综述[J].系统工程与电子技术,2003,25(12): 1488-1491.
[14] Vanegas L V, Labib A W. Fuzzy approaches to evaluation in engineering design[J]. ASME Journal ofMechanical Design, 2005, 127(1): 24-33.
[15] Antonsson E K, Otto K N. Imprecision in engineering design[J]. Journal of Mechanical Design, 1995,117(B): 25-32.
[16] Hsiao S W. Fuzzy logic based decision model for product design[J]. International Journal of Industrial Ergonomics, 1998, 21(2): 103-116.
[17] Thurston D L, Carnahan J V. Fuzzy ratings and utility analysis in preliminary design evaluation of multiple attributes[J]. Journal of Mechanical Design, 1992, 114(4): 648-658.
[18] Carnahan V Thurston D L, Liu T. fuzzing ratings for multiattribute design decision-making[J]. ASME Journal of Mechanical Design, 2004, 116(2): 511-521.
[19] Wang J. A fuzzy outranking method for conceptual design evaluation. International Journal of Production Research[J], 2004, 35(4): 995-1010.
[20] Zhou M. Fuzzy logic and optimization models for implementing QFD[J]. Computers and Industrial Engineering, 1998, 35(1): 237-240.
[21] Vanegas L V, Labib A W. Application of new fuzzy-weighted average (NFWA) method to engineering design evaluation. [J]. International Journal of Production Research, 2001, 39(6): 1147-1162.
[22] Liu H, Wu Z. Automated scheme adjustment for conceptual aircraft design and optimization. 43rd AIAA Aerospace Sciences Meeting and Exhibit, Reno, USA, 2005: 10-13.
[23] 金菊良,杨晓华等. 基于模糊优先关系矩阵的系统评价方法[J]. 系 统 工 程 理 论 方 法 应 用,2005, 8(1): 364-368.
[24] 成经平.机械系统概念设计的机构选型模糊综合评价[J].机械设计与研究,2001, 17(4): 15-17.
[25] Saaty T L, Vargas L G. Decision Making in Economic, Political, Social, and Technological Environments with the Analytic Hierarchy Process[J]. Pittsburgh: RWS Publications, 1994.
[26] Chan F T S, Abhary K. Design and evaluation of automated cellular manufacturing systems with simulation modelling and AHP approach: a case study[J]. Integrated Manufacturing Systems, 1996, 7(6):39-52.
[27] Ayag Z. An integrated approach to evaluating conceptual design alternatives in a new development environment[J]. International Journal of Production Research, 2005, 43(4): 687-713.
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