Multi-objective analysis of a component-based representation within an interactive evolutionary design system

被引:6
作者
Machwe, A. T. [1 ]
Parmee, I. C. [1 ]
机构
[1] Univ W England, ACDDM Grp, Fac Comp Engn & Math Sci, Bristol BS16 1QY, Avon, England
关键词
multi-objective evolutionary algorithms; interactive evolutionary design systems; representation; clustering;
D O I
10.1080/03052150701391041
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This article describes research relating to a user-centered evolutionary design system that evaluates both engineering and aesthetic aspects of design solutions during early-stage conceptual design. The experimental system comprises several components relating to user interaction, problem representation, evolutionary search and exploration and online learning. The main focus of the article is the evolutionary aspect of the system when using a single quantitative objective function plus subjective judgment of the user. Additionally, the manner in which the user-interaction aspect affects system output is assessed by comparing Pareto frontiers generated with and without user interaction via a multi-objective evolutionary algorithm (MOEA). A solution clustering component is also introduced and it is shown how this can improve the level of support to the designer when dealing with a complex design problem involving multiple objectives. Supporting results are from the application of the system to the design of urban furniture which, in this case, largely relates to seating design.
引用
收藏
页码:591 / 613
页数:23
相关论文
共 25 条
  • [1] Branke J., 2005, KNOWLEDGE INCORPORAT
  • [2] CARNAHAN B, 2004, GENETIC EVOLUTIONARY, P433
  • [3] DEB K, 2001, MULTI OBJECTIVE USIN
  • [4] EIBEN AE, 2003, SPRINGER NATURAL COM
  • [5] AN EVOLUTIONARY APPROACH TO THE TRAVELING SALESMAN PROBLEM
    FOGEL, DB
    [J]. BIOLOGICAL CYBERNETICS, 1988, 60 (02) : 139 - 144
  • [6] An Overview of Evolutionary Algorithms in Multiobjective Optimization
    Fonseca, Carlos M.
    Fleming, Peter J.
    [J]. EVOLUTIONARY COMPUTATION, 1995, 3 (01) : 1 - 16
  • [7] Graf J, 1995, ARTIFICIAL NEURAL NETS AND GENETIC ALGORITHMS, P227
  • [8] Kim HS, 2001, IEEE C EVOL COMPUTAT, P887, DOI 10.1109/CEC.2001.934284
  • [9] MACHWE A, 2007, EVO INTERACT, P449
  • [10] MACHWE A, 2006, C EV COMP