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Design optimisation using advanced artificial intelligent system coupled to hybrid-game strategies

Lee, D-S., Gonzalez, L. F., Periuax, J., & Bugeda, G. (2009) Design optimisation using advanced artificial intelligent system coupled to hybrid-game strategies. In Negnevistsky, M. (Ed.) Proceedings of the 3rd International Workshop on Artificial Intelligence in Science and Technology (AISAT 2009), The University of Tasmania, University of Tasmania, Hobart, Tasmania, pp. 1-10.

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    Official URL: http://www.eng.utas.edu.au/conferences/AISAT/aisat...

    Abstract

    One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.

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    ID Code: 33042
    Item Type: Conference Paper
    Keywords: Hybid Games, Optimisation, MDO, Artificial Intelligence
    ISBN: 9781862955509
    Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > NUMERICAL AND COMPUTATIONAL MATHEMATICS (010300) > Optimisation (010303)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Flight Dynamics (090106)
    Divisions: QUT Faculties and Divisions > Faculty of Built Environment and Engineering
    Schools > School of Engineering Systems
    Copyright Owner: Copyright 2009 Artificial Intelligence in Science and Technology
    Deposited On: 12 Jul 2010 10:51
    Last Modified: 11 Aug 2011 02:49

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