REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACE
Genetic Algorithm (GA), a stochastic optimization technique, doesn’t ensure optimal solution every time. Nowadays there is a need to improve the performance of each and every application so that the time required for obtaining quality solution can be minimized. This paper gives a brief overview of t...
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doaj-659fb0a7b3394909a051653906532b122020-11-25T02:15:05ZengICT Academy of Tamil NaduICTACT Journal on Soft Computing0976-65612229-69562013-07-0134615622REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACEA. J. Umbarkar0M. S. Joshi1Department of Information Technology, Walchand College of Engineering, IndiaDepartment of Computer Science and Engineering, Jawaharlal Nehru Engineering College, IndiaGenetic Algorithm (GA), a stochastic optimization technique, doesn’t ensure optimal solution every time. Nowadays there is a need to improve the performance of each and every application so that the time required for obtaining quality solution can be minimized. This paper gives a brief overview of theoretical advances and computing trends, particularly population diversity in PGA (Parallel GA) and provides information about how various authors, researchers, scientists have parallelized GA over various parallel computing paradigms viz. Cluster, MPP (Massively Parallel Processing), GPGPU (General purpose Graphics Processing Units), Grid, Cloud, Multicore/HPC to ensure more optimal solution every time with efficacy and efficiency.http://ictactjournals.in/paper/IJSCPaper_7_615to622.pdfGenetic Algorithm (GA)Parallel GA (PGA)General Purpose Graphics Processing Unit (GPGPU)Massively Parallel Processor (MPP)Population DiversityCloudGridClusterHPC |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. J. Umbarkar M. S. Joshi |
spellingShingle |
A. J. Umbarkar M. S. Joshi REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACE ICTACT Journal on Soft Computing Genetic Algorithm (GA) Parallel GA (PGA) General Purpose Graphics Processing Unit (GPGPU) Massively Parallel Processor (MPP) Population Diversity Cloud Grid Cluster HPC |
author_facet |
A. J. Umbarkar M. S. Joshi |
author_sort |
A. J. Umbarkar |
title |
REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACE |
title_short |
REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACE |
title_full |
REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACE |
title_fullStr |
REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACE |
title_full_unstemmed |
REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACE |
title_sort |
review of parallel genetic algorithm based on computing paradigm and diversity in search space |
publisher |
ICT Academy of Tamil Nadu |
series |
ICTACT Journal on Soft Computing |
issn |
0976-6561 2229-6956 |
publishDate |
2013-07-01 |
description |
Genetic Algorithm (GA), a stochastic optimization technique, doesn’t ensure optimal solution every time. Nowadays there is a need to improve the performance of each and every application so that the time required for obtaining quality solution can be minimized. This paper gives a brief overview of theoretical advances and computing trends, particularly population diversity in PGA (Parallel GA) and provides information about how various authors, researchers, scientists have parallelized GA over various parallel computing paradigms viz. Cluster, MPP (Massively Parallel Processing), GPGPU (General purpose Graphics Processing Units), Grid, Cloud, Multicore/HPC to ensure more optimal solution every time with efficacy and efficiency. |
topic |
Genetic Algorithm (GA) Parallel GA (PGA) General Purpose Graphics Processing Unit (GPGPU) Massively Parallel Processor (MPP) Population Diversity Cloud Grid Cluster HPC |
url |
http://ictactjournals.in/paper/IJSCPaper_7_615to622.pdf |
work_keys_str_mv |
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