Asymptotic convergence of a simulated annealing algorithm for multiobjective optimization problems

In this paper we consider a simulated annealing algorithm for multiobjective optimization problems. With a suitable choice of the acceptance probabilities, the algorithm is shown to converge asymptotically, that is, the Markov chain that describes the algorithm converges with probability one to the Pareto optimal set. Copyright Springer-Verlag 2006

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Year of publication:	2006
Authors:	Villalobos-Arias, Mario ; Coello, Carlos ; Hernández-Lerma, Onésimo
Published in:	Computational Statistics. - Springer. - Vol. 64.2006, 2, p. 353-362
Publisher:	Springer
Subject:	Simulated annealing \| Multiple objective programming \| Multiobjective optimization \| Vector optimization \| Convergence

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

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