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Parallel imperialist competitive algorithms
Abo Akad Univ, Finland..
Univ Turku, Finland..
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
Univ Turku, Finland..
Vise andre og tillknytning
2018 (engelsk)Inngår i: Concurrency and Computation, ISSN 1532-0626, E-ISSN 1532-0634, Vol. 30, nr 7, artikkel-id e4393Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The importance of optimization and NP-problem solving cannot be overemphasized. The usefulness and popularity of evolutionary computing methods are also well established. There are various types of evolutionary methods; they are mostly sequential but some of them have parallel implementations as well. We propose a multi-population method to parallelize the Imperialist Competitive Algorithm. The algorithm has been implemented with the Message Passing Interface on 2 computer platforms, and we have tested our method based on shared memory and message passing architectural models. An outstanding performance is obtained, demonstrating that the proposed method is very efficient concerning both speed and accuracy. In addition, compared with a set of existing well-known parallel algorithms, our approach obtains more accurate results within a shorter time period.

sted, utgiver, år, opplag, sider
WILEY , 2018. Vol. 30, nr 7, artikkel-id e4393
Emneord [en]
evolutionary computing, ICA, multi-population, parallel approaches, parallel programming, optimization, super-linear performance
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-38895DOI: 10.1002/cpe.4393ISI: 000426769200006Scopus ID: 2-s2.0-85040727651OAI: oai:DiVA.org:mdh-38895DiVA, id: diva2:1194220
Tilgjengelig fra: 2018-03-29 Laget: 2018-03-29 Sist oppdatert: 2018-09-18bibliografisk kontrollert

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