Authors: Rudolph, Günter
Title: On a Multi-Objective Evolutionary Algorithm and Its Convergence to the Pareto Set
Language (ISO): en
Abstract: Although there are many versions of evolutionary algorithms that are tailored to multi-criteria optimization, theoretical results are apparently not yet available. Here, it is shown that results known from the theory of evolutionary algorithms in case of single criterion optimization do not carry over to the multi-criterion case. At first, three different step size rules are investigated numerically for a selected problem with two conflicting objectives. The empirical results obtained by these experiments lead to the observation that only one of these step size rules may have the property to ensure convergence to the Pareto set. A theoretical analysis finally shows that a special version of an evolutionary algorithm with this step size rule converges with probability one to the Pareto set for the test problem under consideration.
Subject Headings: evolutionary algorithms
multi-criteria optimization
stochastic convergence to Pareto set
URI: http://hdl.handle.net/2003/5338
http://dx.doi.org/10.17877/DE290R-14970
Issue Date: 1998-11-08
Publisher: Universität Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 531

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