A4 Refereed article in a conference publication
Multi-Population Parallel Imperialist Competitive Algorithm for Solving Systems of Nonlinear Equations
Authors: Majd A, Abdollahi M, Sahebi G, Abdollahi D, Dancshtalab M, Plosila J, Tenhunen H
Editors: Smari, WW
Conference name: International Conference on High Performance Computing & Simulation
Publishing place: New York, NY
Publication year: 2016
Book title : 2016 International Conference on High Performance Computing & Simulation (HPCS)
Journal name in source: 2016 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS 2016)
First page : 767
Last page: 775
Number of pages: 9
ISBN: 978-1-5090-2089-8
eISBN: 978-1-5090-2088-1
DOI: https://doi.org/10.1109/HPCSim.2016.7568412
the widespreadimportance of optimization and solving NP-hard problems, like solving systems of nonlinear equations, is indisputable in a diverse range of sciences. Vast uses of non-linear equations are undeniable. Some of their applications are in economics, engineering, chemistry, mechanics, medicine, and robotics. There are different types of methods of solving the systems of nonlinear equations. One of the most popular of them is Evolutionary Computing (EC). This paper presents an evolutionary algorithm that is called Parallel Imperialist Competitive Algorithm (PICA) which is based on a multi population technique for solving systems of nonlinear equations. In order to demonstrate the efficiency of the proposed approach, some well-known problems are utilized. The results indicate that the PICA has a high success and a quick convergence rate.
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