Bookcover of Evolutionary Computing Performance via MapReduce Parallel Processing
Booktitle:

Evolutionary Computing Performance via MapReduce Parallel Processing

LAP LAMBERT Academic Publishing (2016-02-16 )

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ISBN-13:

978-3-659-84769-1

ISBN-10:
3659847690
EAN:
9783659847691
Book language:
English
Blurb/Shorttext:
Evolutionary computation (EC) is a method that is ubiquitously used to solve complex computation. Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. Despite these advantages, EC suffers from long execution time due to its parallel nature. Therefore, this research explores the prospect of speeding up the EC algorithms specifically GA and PSO via MapReduce (MR) parallel processing framework. MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of “map and reduce”. The performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. Comparisons between GA via MR and PSO via MR are also established in order to find which EC algorithm scales better via MR parallel processing framework. From the results and analysis obtained from this research, it is established that both GA and PSO can be efficiently parallelized and shows good scalability via MR parallel processing framework.
Publishing house:
LAP LAMBERT Academic Publishing
Website:
https://www.lap-publishing.com/
By (author) :
Ahmad Firdaus Ahmad Fadzil
Number of pages:
164
Published on:
2016-02-16
Stock:
Available
Category:
Application software
Price:
71.90 €
Keywords:
evolutionary computing, genetic algorithm, MapReduce, Parallel Processing, PSO

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