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

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.

[1]  Azahar T. Machwe,et al.  Integrating Aesthetic Criteria with a User-centric Evolutionary System via a Component-based Design Representation , 2005 .

[2]  R. K. Ursem.  Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[3]  J. Gero,et al.  Evolving designs by generating useful complex gene structures , 1999 .

[4]  I. C. Parmee,et al.  Supporting implicit learning via the visualisation of COGA multi-objective data , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[5]  I. C. Parmee,et al.  OVERCOMING REPRESENTATION ISSUES WHEN INCLUDING AESTHETIC CRITERIA IN EVOLUTIONARY DESIGN , 2005 .

[6]  F. Tang,et al.  A polychromatic sets approach to the conceptual design of machine tools , 2005 .

[7]  Hideyuki Takagi,et al.  Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation , 2001, Proc. IEEE.

[8]  Dave Sims,et al.  Decriminalizing the fingerprint , 1994, IEEE Computer Graphics and Applications.

[9]  Jeanine Graf,et al.  Interactve Evolutionary Algorithms in Design , 1995, ICANNGA.

[10]  A. Moshaiov,et al.  Concept-based interactive evolutionary computation for multi-objective path planning , 2004, Second IEEE International Conference on Computational Cybernetics, 2004. ICCC 2004..

[11]  C. J. Moore,et al.  Establishing a knowledge base for bridge aesthetics , 1996 .

[12]  Kalyanmoy Deb,et al.  Integrating User Preferences into Evolutionary Multi-Objective Optimization , 2005 .

[13]  Karl Sims,et al.  Evolving virtual creatures , 1994, SIGGRAPH.

[14]  Ian C. Parmee,et al.  Towards an Interactive, Generative Design System: Integrating a 'Build and Evolve' Approach with Machine Learning for Complex Freeform Design , 2009, EvoWorkshops.

[15]  Marco Laumanns,et al.  SPEA2: Improving the strength pareto evolutionary algorithm , 2001 .

[16]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[17]  Peter J. Fleming,et al.  An Overview of Evolutionary Algorithms in Multiobjective Optimization , 1995, Evolutionary Computation.

[18]  Alice M. Agogino,et al.  Case-based conceptual design information server for concurrent engineering , 1996, Comput. Aided Des..

[19]  Hiromitsu Takagi,et al.  Interactive evolutionary computation: Cooperation of computational intel-ligent and human kansei , 1998 .

[20]  Sung-Bae Cho,et al.  An efficient genetic algorithm with less fitness evaluation by clustering , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[21]  D. Fogel.  An evolutionary approach to the traveling salesman problem , 1988, Biological Cybernetics.

[22]  Ian C. Parmee,et al.  Integrating aesthetic criteria with evolutionary processes in complex, free-form design – an initial investigation , 2006, 2006 IEEE International Conference on Evolutionary Computation.