Parallel Improvements of the Jaya Optimization Algorithm

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Title: Parallel Improvements of the Jaya Optimization Algorithm
Authors: Migallón Gomis, Héctor | Jimeno-Morenilla, Antonio | Sanchez-Romero, Jose-Luis
Research Group/s: UniCAD: Grupo de investigación en CAD/CAM/CAE de la Universidad de Alicante
Center, Department or Service: Universidad de Alicante. Departamento de Tecnología Informática y Computación
Keywords: Jaya | Optimization problems | Parallel | Heuristic | OpenMP | MPI | Hybrid MPI/OpenMP
Knowledge Area: Arquitectura y Tecnología de Computadores
Issue Date: 18-May-2018
Publisher: MDPI
Citation: Migallón H, Jimeno-Morenilla A, Sanchez-Romero J-L. Parallel Improvements of the Jaya Optimization Algorithm. Applied Sciences. 2018; 8(5):819. doi:10.3390/app8050819
Abstract: A wide range of applications use optimization algorithms to find an optimal value, often a minimum one, for a given function. Depending on the application, both the optimization algorithm’s behavior, and its computational time, can prove to be critical issues. In this paper, we present our efficient parallel proposals of the Jaya algorithm, a recent optimization algorithm that enables one to solve constrained and unconstrained optimization problems. We tested parallel Jaya algorithms for shared, distributed, and heterogeneous memory platforms, obtaining good parallel performance while leaving Jaya algorithm behavior unchanged. Parallel performance was analyzed using 30 unconstrained functions reaching a speed-up of up to 57.6x using 60 processors. For all tested functions, the parallel distributed memory algorithm obtained parallel efficiencies that were nearly ideal, and combining it with the shared memory algorithm allowed us to obtain good parallel performance. The experimental results show a good parallel performance regardless of the nature of the function to be optimized.
Sponsor: This research was supported by the Spanish Ministry of Economy and Competitiveness under Grants TIN2015-66972-C5-4-R and TIN2017-89266-R, co-financed by FEDER funds (MINECO/FEDER/UE).
URI: http://hdl.handle.net/10045/75695
ISSN: 2076-3417
DOI: 10.3390/app8050819
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Peer Review: si
Publisher version: https://doi.org/10.3390/app8050819
Appears in Collections:INV - UNICAD - Artículos de Revistas

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