A4 Refereed article in a conference publication
PICA: Multi-Population Implementation of Parallel Imperialist Competitive Algorithms
Authors: Majd A, Lotfi S, Sahebi G, Daneshtalab M, Plosila J
Editors: Yiannis Cotronis, Masoud Daneshtalab, George Angelos Papadopoulos
Conference name: Euromicro International Conference on Parallel, Distributed, and Network-Based Processing
Publication year: 2016
Book title : 2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)
Journal name in source: 2016 24TH EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, AND NETWORK-BASED PROCESSING (PDP)
Journal acronym: EUROMICRO WORKSHOP P
Series title: Euromicro Conference on Parallel Distributed and Network-Based Processing
First page : 248
Last page: 255
Number of pages: 8
eISBN: 978-1-4673-8776-7
ISSN: 1066-6192
DOI: https://doi.org/10.1109/PDP.2016.93
The importance of optimization and NP problems solving cannot be over emphasized. The usefulness and popularity of evolutionary computing methods are also well established. There are various types of evolutionary methods that arc mostly sequential, and some others have parallel implementation. We propose a method to parallelize Imperialist Competitive Algorithm (Multi-Population). The algorithm has been implemented with MPI on two platforms and have tested our algorithms on a shared- memory and message passing architecture. An outstanding performance is obtained, which indicates that the method is efficient concern to speed and accuracy. In the second step, the proposed algorithm is compared with a set of existing well known parallel algorithms and is indicated that it obtains more accurate solutions in a lower time.
