An Adaptive Local Search Algorithm for Real-Valued Dynamic Optimization

dc.cclicenceCC-BY-NCen
dc.contributor.authorMavrovouniotis, Michalisen
dc.contributor.authorNeri, Ferranteen
dc.contributor.authorYang, Shengxiangen
dc.date.accessioned2016-04-13T15:06:34Z
dc.date.available2016-04-13T15:06:34Z
dc.date.issued2015-05
dc.description.abstractThis paper proposes a novel adaptive local search algorithm for tackling real-valued (or continuous) dynamic optimization problems. The proposed algorithm is a simple single-solution based metaheuristic that perturbs the variables separately to select the search direction for the following step and adapts its step size to the gradient. The search directions that appear to be the most promising are rewarded by a step size increase while the unsuccessful moves attempt to reverse the search direction with a reduced step size. When the environment is subject to changes, a new solution is sampled and crosses over the best solution in the previous environment. Furthermore, the algorithm makes use of a small archive where the best solutions are saved. Experimental results show that the proposed algorithm, despite its simplicity, is competitive with complex population-based algorithms for tested dynamic optimization problems.en
dc.explorer.multimediaNoen
dc.funderEPSRC (Engineering and Physical Sciences Research Council)en
dc.identifier.citationMavrovouniotis, M., Neri, F. and Yang, S. (2015) An adaptive local search algorithm for real-valued dynamic optimization. Proceedings of the 2015 IEEE Congress on Evolutionary Computation, pp. 1388-1395en
dc.identifier.doihttps://doi.org/10.1109/CEC.2015.7257050
dc.identifier.issn1089-778X
dc.identifier.urihttp://hdl.handle.net/2086/11884
dc.language.isoen_USen
dc.peerreviewedYesen
dc.projectidEP/K001310/1en
dc.publisherIEEE Pressen
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.subjectAdaptive local searchen
dc.subjectdynamic optimization problemsen
dc.titleAn Adaptive Local Search Algorithm for Real-Valued Dynamic Optimizationen
dc.typeConferenceen

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