Abstract
This paper presents the asymptotic convergence analysis of Simulated Annealing, an Artificial Immune System and a General Evolutionary Algorithm for multiobjective optimization problems. In the case of a General Evolutionary Algorithm, we refer to any algorithm in which the transition probabilities use a uniform mutation rule. We prove that these algorithms converge if elitism is used.
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Villalobos-Arias, M., Coello, C.A.C., Hernández-Lerma, O. (2005). Asymptotic Convergence of Some Metaheuristics Used for Multiobjective Optimization. In: Wright, A.H., Vose, M.D., De Jong, K.A., Schmitt, L.M. (eds) Foundations of Genetic Algorithms. FOGA 2005. Lecture Notes in Computer Science, vol 3469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11513575_6
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DOI: https://doi.org/10.1007/11513575_6
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