REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACE

Autor:	A. J. Umbarkar, M. S. Joshi
Jazyk:	angličtina
Rok vydání:	2013
Předmět:	Genetic Algorithm (GA) Parallel GA (PGA) General Purpose Graphics Processing Unit (GPGPU) Massively Parallel Processor (MPP) Population Diversity Cloud Grid Cluster HPC Computer engineering. Computer hardware TK7885-7895
Zdroj:	ICTACT Journal on Soft Computing, Vol 3, Iss 4, Pp 615-622 (2013)
Druh dokumentu:	article
ISSN:	0976-6561 2229-6956
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/659fb0a7b3394909a051653906532b12 Zobrazit plný text záznamu View record in DOAJ