caa a22 4500 605470731 CHVBK 20210128100329.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00500-014-1477-4 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1477-4 A directed search strategy for evolutionary dynamic multiobjective optimization [Elektronische Daten] [Yan Wu, Yaochu Jin, Xiaoxiong Liu] Many real-world multiobjective optimization problems are dynamic, requiring an optimization algorithm that is able to continuously track the moving Pareto front over time. In this paper, we propose a directed search strategy (DSS) consisting of two mechanisms for improving the performance of multiobjective evolutionary algorithms in changing environments. The first mechanism reinitializes the population based on the predicted moving direction as well as the directions that are orthogonal to the moving direction of the Pareto set, when a change is detected. The second mechanism aims to accelerate the convergence by generating solutions in predicted regions of the Pareto set according to the moving direction of the non-dominated solutions between two consecutive generations. The two mechanisms, when combined together, are able to achieve a good balance between exploration and exploitation for evolutionary algorithms to solve dynamic multiobjective optimization problems. We compare DSS with two existing prediction strategies on a variety of test instances having different changing dynamics. Empirical results show that DSS is powerful for evolutionary algorithms to deal with dynamic multiobjective optimization problems. Springer-Verlag Berlin Heidelberg, 2014 Dynamic multiobjective optimization nationallicence Evolutionary algorithm nationallicence Prediction nationallicence Local search nationallicence Wu Yan School of Mathematics and Statistics, Xidian University, 710071, Xian, China aut Jin Yaochu Department of Computing, University of Surrey, GU2 7XH, Guildford, UK aut Liu Xiaoxiong School of Automation, Northwestern Polytechnical University, 710072, Xian, China aut Soft Computing Springer Berlin Heidelberg 19/11(2015-11-01), 3221-3235 1432-7643 19:11<3221 2015 19 500 https://doi.org/10.1007/s00500-014-1477-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1477-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wu Yan School of Mathematics and Statistics, Xidian University, 710071, Xian, China aut NATIONALLICENCE 700 1- Jin Yaochu Department of Computing, University of Surrey, GU2 7XH, Guildford, UK aut NATIONALLICENCE 700 1- Liu Xiaoxiong School of Automation, Northwestern Polytechnical University, 710072, Xian, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/11(2015-11-01), 3221-3235 1432-7643 19:11<3221 2015 19 500