Matches in SemOpenAlex for { <https://semopenalex.org/work/W2849751101> ?p ?o ?g. }
- W2849751101 endingPage "3520" @default.
- W2849751101 startingPage "3507" @default.
- W2849751101 abstract "Cooperative coevolutionary (CC) algorithms decompose a problem into several subcomponents and optimize them separately. Such a divide-and-conquer strategy makes CC algorithms potentially well suited for large-scale optimization. However, decomposition may be inaccurate, resulting in a wrong division of the interacting decision variables into different subcomponents and thereby a loss of important information about the topology of the overall fitness landscape. In this paper, we suggest an idea that concurrently searches for multiple optima and uses them as informative representatives to be exchanged among subcomponents for compensation. To this end, we incorporate a multimodal optimization procedure into each subcomponent, which is adaptively triggered by the status of subcomponent optimizers. In addition, a nondominance-based selection scheme is proposed to adaptively select one complete solution for evaluation from the ones that are constructed by combining informative representatives from each subcomponent with a given solution. The performance of the proposed algorithm has been demonstrated by comparing five popular CC algorithms on a set of selected problems that are recognized to be hard for traditional CC algorithms. The superior performance of the proposed algorithm is further confirmed by a comprehensive study that compares 17 state-of-the-art CC algorithms and other metaheuristic algorithms on 20 1000-dimensional benchmark functions." @default.
- W2849751101 created "2018-07-19" @default.
- W2849751101 creator A5013137993 @default.
- W2849751101 creator A5032314861 @default.
- W2849751101 creator A5091324372 @default.
- W2849751101 date "2019-09-01" @default.
- W2849751101 modified "2023-10-03" @default.
- W2849751101 title "Multimodal Optimization Enhanced Cooperative Coevolution for Large-Scale Optimization" @default.
- W2849751101 cites W120185646 @default.
- W2849751101 cites W1485910948 @default.
- W2849751101 cites W1555689267 @default.
- W2849751101 cites W1779658280 @default.
- W2849751101 cites W1825719191 @default.
- W2849751101 cites W1983947028 @default.
- W2849751101 cites W1986345851 @default.
- W2849751101 cites W1994739843 @default.
- W2849751101 cites W1995972800 @default.
- W2849751101 cites W1996673440 @default.
- W2849751101 cites W1996936486 @default.
- W2849751101 cites W1998155577 @default.
- W2849751101 cites W2012452381 @default.
- W2849751101 cites W2013497292 @default.
- W2849751101 cites W2017426530 @default.
- W2849751101 cites W2018375997 @default.
- W2849751101 cites W2021418037 @default.
- W2849751101 cites W2042476863 @default.
- W2849751101 cites W2043816158 @default.
- W2849751101 cites W2045050140 @default.
- W2849751101 cites W2061706483 @default.
- W2849751101 cites W2063375245 @default.
- W2849751101 cites W2067936154 @default.
- W2849751101 cites W2070972695 @default.
- W2849751101 cites W2071694551 @default.
- W2849751101 cites W2078617346 @default.
- W2849751101 cites W2078702416 @default.
- W2849751101 cites W2081524587 @default.
- W2849751101 cites W2095554186 @default.
- W2849751101 cites W2096166399 @default.
- W2849751101 cites W2099129608 @default.
- W2849751101 cites W2100404317 @default.
- W2849751101 cites W2101677491 @default.
- W2849751101 cites W2105511939 @default.
- W2849751101 cites W2121429049 @default.
- W2849751101 cites W2123859926 @default.
- W2849751101 cites W2126105956 @default.
- W2849751101 cites W2137143026 @default.
- W2849751101 cites W2145418868 @default.
- W2849751101 cites W2149848331 @default.
- W2849751101 cites W2155005783 @default.
- W2849751101 cites W2155529731 @default.
- W2849751101 cites W2159308419 @default.
- W2849751101 cites W2160615157 @default.
- W2849751101 cites W2163647484 @default.
- W2849751101 cites W2165533158 @default.
- W2849751101 cites W2165626989 @default.
- W2849751101 cites W2165687335 @default.
- W2849751101 cites W2171074980 @default.
- W2849751101 cites W2269421492 @default.
- W2849751101 cites W2271253903 @default.
- W2849751101 cites W2312599005 @default.
- W2849751101 cites W2329749247 @default.
- W2849751101 cites W2345476775 @default.
- W2849751101 cites W2413634576 @default.
- W2849751101 cites W2468972411 @default.
- W2849751101 cites W2510493362 @default.
- W2849751101 doi "https://doi.org/10.1109/tcyb.2018.2846179" @default.
- W2849751101 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29994626" @default.
- W2849751101 hasPublicationYear "2019" @default.
- W2849751101 type Work @default.
- W2849751101 sameAs 2849751101 @default.
- W2849751101 citedByCount "35" @default.
- W2849751101 countsByYear W28497511012019 @default.
- W2849751101 countsByYear W28497511012020 @default.
- W2849751101 countsByYear W28497511012021 @default.
- W2849751101 countsByYear W28497511012022 @default.
- W2849751101 countsByYear W28497511012023 @default.
- W2849751101 crossrefType "journal-article" @default.
- W2849751101 hasAuthorship W2849751101A5013137993 @default.
- W2849751101 hasAuthorship W2849751101A5032314861 @default.
- W2849751101 hasAuthorship W2849751101A5091324372 @default.
- W2849751101 hasConcept C109718341 @default.
- W2849751101 hasConcept C11413529 @default.
- W2849751101 hasConcept C124681953 @default.
- W2849751101 hasConcept C126255220 @default.
- W2849751101 hasConcept C13280743 @default.
- W2849751101 hasConcept C137836250 @default.
- W2849751101 hasConcept C154945302 @default.
- W2849751101 hasConcept C177264268 @default.
- W2849751101 hasConcept C185798385 @default.
- W2849751101 hasConcept C18903297 @default.
- W2849751101 hasConcept C199360897 @default.
- W2849751101 hasConcept C205649164 @default.
- W2849751101 hasConcept C33923547 @default.
- W2849751101 hasConcept C41008148 @default.
- W2849751101 hasConcept C71559656 @default.
- W2849751101 hasConcept C81917197 @default.
- W2849751101 hasConcept C86803240 @default.
- W2849751101 hasConceptScore W2849751101C109718341 @default.