A runtime analysis of evolutionary algorithms for constrained optimization problems

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dc.contributor.author He, Jun
dc.contributor.author Zhou, Yuren
dc.date.accessioned 2008-12-18T11:31:40Z
dc.date.available 2008-12-18T11:31:40Z
dc.date.issued 2008-12-18
dc.identifier.citation He , J & Zhou , Y 2008 , ' A runtime analysis of evolutionary algorithms for constrained optimization problems ' IEEE Transactions on Evolutionary Computation , pp. 608-619 . en
dc.identifier.other PURE: 105549
dc.identifier.other dspace: 2160/1778
dc.identifier.uri http://hdl.handle.net/2160/1778
dc.description He, J., Zhou, Y., A runtime analysis of evolutionary algorithms for constrained optimization problems, IEEE Transactions on Evolutionary Computation, 11(5) pp.608-619 en
dc.description.abstract though there are many evolutionary algorithms (EAs) for solving constrained optimization problems, there are few rigorous theoretical analyses. This paper presents a time complexity analysis of EAs for solving constrained optimization. It is shown when the penalty coefficient is chosen properly, direct comparison between pairs of solutions using penalty fitness function is equivalent to that using the criteria ldquosuperiority of feasible pointrdquo or ldquosuperiority of objective function value.rdquo This paper analyzes the role of penalty coefficients in EAs in terms of time complexity. The results show that in some examples, EAs benefit greatly from higher penalty coefficients, while in other examples, EAs benefit from lower penalty coefficients. This paper also investigates the runtime of EAs for solving the 0-1 knapsack problem and the results indicate that the mean first hitting times ranges from a polynomial-time to an exponential time when different penalty coefficients are used. en
dc.format.extent 12 en
dc.language.iso eng
dc.relation.ispartof IEEE Transactions on Evolutionary Computation en
dc.title A runtime analysis of evolutionary algorithms for constrained optimization problems en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.contributor.institution Department of Computer Science en
dc.description.status Peer reviewed en


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