Varying fitness functions in genetic algorithm constrained optimization: the cutting stock and unit commitment problems
- 1 January 1998
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
- Vol. 28 (5) , 629-640
- https://doi.org/10.1109/3477.718514
Abstract
In this paper, we present a specific varying fitness function technique in genetic algorithm (GA) constrained optimization. This technique incorporates the problem's constraints into the fitness function in a dynamic way. It consists in forming a fitness function with varying penalty terms. The resulting varying. fitness function facilitates the GA search. The performance of the technique is tested on two optimization problems: the cutting stock, and the unit commitment problems. Also, new domain-specific operators are introduced. Solutions-obtained by means of the varying and the conventional (nonvarying) fitness function techniques are compared. results show the superiority of the proposed technique.Keywords
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