Estimation of distribution algorithm combined with chaotic sequence for dynamic optimisation problems. (2017)

• Record Type: Journal Article
• Authors: Yu, Fahong; Li, Wenping; Tao, Jiang; Deng, Kun; Ma, Longhua; He, Feng
• Is Part Of: International journal of computing science and mathematics. Volume 8:Number 1(2017)
• Page Start: 12
• Page End: 19
• Publication Date: 2017
• Subjects: estimation of distribution algorithms -- EDA -- chaotic sequences -- dynamic optimisation -- population diversity -- local search -- chaos; Mathematics -- Periodicals; Computer science -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.285
• Languages: English
• ISSNs: 1752-5055

Abstract

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.