Matches in SemOpenAlex for { <https://semopenalex.org/work/W4366286072> ?p ?o ?g. }
- W4366286072 endingPage "120184" @default.
- W4366286072 startingPage "120184" @default.
- W4366286072 abstract "Large-scale multi-objective optimization problems (LSMOPs) bring significant challenges due to their large number of decision variables. Most of the existing algorithms fail to obtain high-quality solutions for the LSMOPs. To remedy this issue, an algorithm named dual-stage large-scale multi-objective evolutionary algorithm with dynamic learning strategy (DLMOEA-DLS) is proposed in this paper. In the DLMOEA-DLS, the entire evolution process mainly includes two stages, and each stage plays a different role in the searching process. In the first stage, the decision variables are clustering into two categories to be optimized independently for the convergence of the population. In the second stage, a dynamic learning strategy is designed to generate new offspring, in which each solution learns from a leader with better fitness and coupled control parameter for each solution is adaptively updated by learning from the historical behaviors of the solution. Moreover, an environmental selection operator is adopted to reserve promising solutions for the next iteration. To verify the performance of the DLMOEA-DLS, five state-of-the-art algorithms are used for comparison on 36 LSMOP benchmark instances, 48 LMF benchmark instances, and 6 real-world TREE benchmark instances. The experimental results demonstrate the superiority of the DLMOEA-DLS over the five state-of-the-art algorithms." @default.
- W4366286072 created "2023-04-20" @default.
- W4366286072 creator A5009567610 @default.
- W4366286072 creator A5044913343 @default.
- W4366286072 creator A5055550759 @default.
- W4366286072 creator A5060815634 @default.
- W4366286072 date "2023-09-01" @default.
- W4366286072 modified "2023-10-06" @default.
- W4366286072 title "A dual-stage large-scale multi-objective evolutionary algorithm with dynamic learning strategy" @default.
- W4366286072 cites W1833634424 @default.
- W4366286072 cites W1995972800 @default.
- W4366286072 cites W2085830763 @default.
- W4366286072 cites W2126105956 @default.
- W4366286072 cites W2128357515 @default.
- W4366286072 cites W2137340504 @default.
- W4366286072 cites W2143381319 @default.
- W4366286072 cites W2145418868 @default.
- W4366286072 cites W2146713522 @default.
- W4366286072 cites W2162145193 @default.
- W4366286072 cites W2329749247 @default.
- W4366286072 cites W2510493362 @default.
- W4366286072 cites W2513211214 @default.
- W4366286072 cites W2567327143 @default.
- W4366286072 cites W2594344284 @default.
- W4366286072 cites W2616257225 @default.
- W4366286072 cites W2621129539 @default.
- W4366286072 cites W2751605210 @default.
- W4366286072 cites W2764251381 @default.
- W4366286072 cites W2766133347 @default.
- W4366286072 cites W2832779309 @default.
- W4366286072 cites W2889094611 @default.
- W4366286072 cites W2894825269 @default.
- W4366286072 cites W2897783557 @default.
- W4366286072 cites W2914542742 @default.
- W4366286072 cites W2932748297 @default.
- W4366286072 cites W2940281941 @default.
- W4366286072 cites W2955147151 @default.
- W4366286072 cites W2996097017 @default.
- W4366286072 cites W2999124658 @default.
- W4366286072 cites W3011505908 @default.
- W4366286072 cites W3013056622 @default.
- W4366286072 cites W3041654307 @default.
- W4366286072 cites W3109051023 @default.
- W4366286072 cites W3120732119 @default.
- W4366286072 cites W3126639668 @default.
- W4366286072 cites W3134440233 @default.
- W4366286072 cites W3138813619 @default.
- W4366286072 cites W3176681481 @default.
- W4366286072 cites W3184173059 @default.
- W4366286072 cites W3200129594 @default.
- W4366286072 cites W3217109289 @default.
- W4366286072 cites W4205874599 @default.
- W4366286072 cites W4206608859 @default.
- W4366286072 cites W4225130893 @default.
- W4366286072 doi "https://doi.org/10.1016/j.eswa.2023.120184" @default.
- W4366286072 hasPublicationYear "2023" @default.
- W4366286072 type Work @default.
- W4366286072 citedByCount "1" @default.
- W4366286072 countsByYear W43662860722023 @default.
- W4366286072 crossrefType "journal-article" @default.
- W4366286072 hasAuthorship W4366286072A5009567610 @default.
- W4366286072 hasAuthorship W4366286072A5044913343 @default.
- W4366286072 hasAuthorship W4366286072A5055550759 @default.
- W4366286072 hasAuthorship W4366286072A5060815634 @default.
- W4366286072 hasConcept C111919701 @default.
- W4366286072 hasConcept C11413529 @default.
- W4366286072 hasConcept C119857082 @default.
- W4366286072 hasConcept C121332964 @default.
- W4366286072 hasConcept C124952713 @default.
- W4366286072 hasConcept C126255220 @default.
- W4366286072 hasConcept C13280743 @default.
- W4366286072 hasConcept C142362112 @default.
- W4366286072 hasConcept C144024400 @default.
- W4366286072 hasConcept C149923435 @default.
- W4366286072 hasConcept C154945302 @default.
- W4366286072 hasConcept C159149176 @default.
- W4366286072 hasConcept C162324750 @default.
- W4366286072 hasConcept C185798385 @default.
- W4366286072 hasConcept C205649164 @default.
- W4366286072 hasConcept C2777303404 @default.
- W4366286072 hasConcept C2778755073 @default.
- W4366286072 hasConcept C2780980858 @default.
- W4366286072 hasConcept C2908647359 @default.
- W4366286072 hasConcept C33923547 @default.
- W4366286072 hasConcept C41008148 @default.
- W4366286072 hasConcept C50522688 @default.
- W4366286072 hasConcept C62520636 @default.
- W4366286072 hasConcept C73555534 @default.
- W4366286072 hasConcept C98045186 @default.
- W4366286072 hasConceptScore W4366286072C111919701 @default.
- W4366286072 hasConceptScore W4366286072C11413529 @default.
- W4366286072 hasConceptScore W4366286072C119857082 @default.
- W4366286072 hasConceptScore W4366286072C121332964 @default.
- W4366286072 hasConceptScore W4366286072C124952713 @default.
- W4366286072 hasConceptScore W4366286072C126255220 @default.
- W4366286072 hasConceptScore W4366286072C13280743 @default.
- W4366286072 hasConceptScore W4366286072C142362112 @default.
- W4366286072 hasConceptScore W4366286072C144024400 @default.