Conference Paper

Multi-objective Parallel Tabu Search.

In proceeding of: Parallel Problem Solving from Nature - PPSN VIII, 8th International Conference, Birmingham, UK, September 18-22, 2004, Proceedings
Source: DBLP
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    ABSTRACT: This paper studies the effectiveness of incorporating co-operative co-evolutionary strategy into 4 evolutionary multi-objective optimisation algorithms – MOGA, NPGA, NSGA and CNSGA – for continuum topology design. Apart from the co-operative co-evolutionary concept, the algorithms employ the elitism and crowding distance techniques to promote the diversity within the set of preserved non-dominated solutions. Three-related 2D heat conduction problems with two design objectives are used as the case studies. The proposed co-operative co-evolution is found to improve the optimisation effectiveness significantly. The species arrangements and sizes have some impacts; the use of moderately small species barely improves the search performances due to the interference from species coupling. As these effects depend on physical meanings of problems, it is more expedient to estimate the parameters in practice.
    Computer-Aided Design and Applications 01/2005; 2:487-496.