Estimation of distribution algorithm combined with chaotic sequence for dynamic optimisation problems
type: Item
instance of: scholarly article
title: Estimation of distribution algorithm combined with chaotic sequence for dynamic optimisation problems
zbMATH Open document ID: 1453.90223
DOI: 10.1504/IJCSM.2017.083140
author: Yanyan Li
published in: International Journal of Computing Science and Mathematics
publication date: 2021-02-03T00:00:00Z
review text: Summary: To track the optima in dynamic environments with estimation of distribution algorithm, maintenance of the diversity of the population is an essential requirement. Taking this point into consideration, this paper proposes an estimation of distribution algorithm combined with a chaotic sequence (CEDA) for dynamic optimisation problems. In CEDA, a chaotic sequence is introduced to maintain the diversity of population and enhance improve the local search ability. Many numerical experiments are reported in order to compare the performance of the CEDA with the self-adaptive approach by other authors. The numerical results show that the performance of our algorithm is superior to that of other published algorithms on two dynamic benchmark problems.
Mathematics Subject Classification ID: 90C59
zbMATH DE Number: 7305414
zbMATH Keywords: estimation of distribution algorithms
zbMATH Keywords: EDA
zbMATH Keywords: chaotic sequences
zbMATH Keywords: dynamic optimisation
zbMATH Keywords: population diversity
zbMATH Keywords: local search
zbMATH Keywords: chaos
MaRDI profile type: Publication
full work available at URL: ijcsm.2017.083140
OpenAlex ID: W4242307726
description: scientific article