NDLI: Nash genetic algorithms: examples and applications

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Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406)

Nash genetic algorithms: examples and applications

Content Provider	IEEE Xplore Digital Library
Author	Sefrioui, M. Perlaux, J.
Copyright Year	2000
Description	Author affiliation: Paris VI Univ., France (Sefrioui, M.)
Abstract	This article presents both theoretical aspects and experimental results for Nash genetic algorithms. Nash GAs are an alternative for multiple objective optimization as they are an optimization tool based on noncooperative game theory. They are explained in detail, along with the advantages conferred by their equilibrium state. This approach is tested on a few benchmark problems, and some comparisons are made with Pareto GAs, particularly in terms of speed and robustness. The different concepts presented in this paper are then illustrated via experiments on a computational fluid dynamics problem, namely nozzle reconstruction with multiple criteria (subsonic and transonic shocked flows). The overall results are that Nash genetic algorithms offer a fast and robust alternative for multiple objective optimization.
Starting Page	509
Ending Page	516
File Size	618417
Page Count	8
File Format	PDF
ISBN	0780363752
DOI	10.1109/CEC.2000.870339
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-07-16
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms Nash equilibrium Game theory Robustness Merging Benchmark testing Pareto optimization
Content Type	Text
Resource Type	Article

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