Multi-objective parallel tabu search

Book chapter (2004)

Authors

Daniel M. Jaeggi University of Cambridge
Chris Asselin-Miller University of Cambridge
Geoffrey T. Parks University of Cambridge
Timoleon Kipouros University of Cambridge
Theo A. Bell University of Cambridge
P.J. Clarkson University of Cambridge
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Published Date

2004

Language

English

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Abstract

This paper describes the implementation of a parallel Tabu Search algorithm for multi-objective continuous optimisation problems. We compare our new algorithm with a leading multi-objective Genetic Algorithm and find it exhibits comparable performance on standard benchmark problems. In addition, for certain problem types, we expect Tabu Search to outperform other algorithms and present preliminary results from an aerodynamic shape optimisation problem. This is a real-world, highly constrained, computationally demanding design problem which requires efficient optimisation algorithms that can be run on parallel computers: with this approach optimisation algorithms are able to play a part in the design cycle.