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Parallel imperialist competitive algorithms
Author(s) -
Majd Amin,
Sahebi Golnaz,
Daneshtalab Masoud,
Plosila Juha,
Lotfi Shahriar,
Tenhunen Hannu
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4393
Subject(s) - computer science , implementation , message passing interface , parallel computing , imperialist competitive algorithm , message passing , evolutionary algorithm , set (abstract data type) , parallel algorithm , population , shared memory , theoretical computer science , algorithm , optimization problem , artificial intelligence , programming language , multi swarm optimization , demography , sociology
Summary 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.