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Improving metaheuristic performance by evolving a variable fitness function

Yes / In this paper we study a complex real world workforce scheduling
problem. We apply constructive search and variable neighbourhood search
(VNS) metaheuristics and enhance these methods by using a variable fitness
function. The variable fitness function (VFF) uses an evolutionary approach to
evolve weights for each of the (multiple) objectives. The variable fitness
function can potentially enhance any search based optimisation heuristic where
multiple objectives can be defined through evolutionary changes in the search
direction. We show that the VFF significantly improves performance of
constructive and VNS approaches on training problems, and "learn" problem
features which enhance the performance on unseen test problem instances.

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/2498
Date January 2008
CreatorsDahal, Keshav P., Remde, Stephen M., Cowling, Peter I., Colledge, N.J.
PublisherSpringer Verlag
Source SetsBradford Scholars
LanguageEnglish
Detected LanguageEnglish
TypeConference paper, Accepted manuscript
Rights© 2008 Springer Verlag. Reproduced in accordance with the publisher's self-archiving policy. Original publication is available at http://www.springerlink.com, Unspecified

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