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A Simplified Artificial Life Model for Multiobjective Optimisation: A Preliminary Report

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Berry, A and Vamplew, P (2003) A Simplified Artificial Life Model for Multiobjective Optimisation: A Preliminary Report. In: 2003 IEEE Congress on Evolutionary Computation, 8-12 December, 2003, Canberra, Australia.

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Abstract

Recent research in the field of Multiobjective Optimisation (MOO) has been focused on achieving the Pareto optimal front by explicitly analysing the dominance level of individual solutions. While such approaches have produced good results for a variety of problems, they are computationally expensive due to the complexities of deriving the dominance level for each solution against the entire population. TB_MOO (Threshold Based Multiobjective Optimisation) is a new artificial life approach to MOO problems that does not analyse dominance, nor perform any agent-agent comparisons. This reduction in complexity results in a significant decrease in processing overhead. Results show that TB_MOO performs comparably, and often better, than its more complicated counter-parts with respect to distance from the Pareto optimal front, but is slightly weaker in terms of distribution and extent.

Item Type: Conference or Workshop Item (Paper)
Keywords: multi-objective optimisation, artificial life
Date Deposited: 19 Aug 2004
Last Modified: 18 Nov 2014 03:10
URI: http://eprints.utas.edu.au/id/eprint/51
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