Asymptotic convergence of some metaheuristics used for multiobjective optimization

Authors:
Mario Villalobos-Arias;Carlos A. Coello Coello;Onésimo Hernández-Lerma
Affiliations:
Department of Mathematics, CINVESTAV-IPN, México, D.F., Mexico;Depto. de Ingeniería Eléctrica, Sección de Computación, CINVESTAV-IPN, Evolutionary Computation Group, México, D. F., Mexico;Department of Mathematics, CINVESTAV-IPN, México, D.F., Mexico
Venue:
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Year:
2005

Citing 11
Cited 3

Simulated annealing: theory and applications

Simulated annealing: theory and applications
Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing

Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Evolutionary computation: toward a new philosophy of machine intelligence

Evolutionary computation: toward a new philosophy of machine intelligence
Intelligence through simulated evolution: forty years of evolutionary programming

Intelligence through simulated evolution: forty years of evolutionary programming
Evolution and Optimum Seeking: The Sixth Generation

Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Algorithms for Solving Multi-Objective Problems

Evolutionary Algorithms for Solving Multi-Objective Problems
Artificial Immune Systems: A New Computational Intelligence Paradigm

Artificial Immune Systems: A New Computational Intelligence Paradigm
Multiobjective optimization using ideas from the clonal selection principle

GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach

IEEE Transactions on Evolutionary Computation
Learning and optimization using the clonal selection principle

IEEE Transactions on Evolutionary Computation

Molecular dynamics optimizer

EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Exploiting molecular dynamics for multi-objective optimization

Expert Systems with Applications: An International Journal
On set-based multiobjective optimization

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

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.