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Binary Particle Swarm Optimization with Crossover Operation for Discrete Optimization

by Deepak Singh, Vikas Singh, Uzma Ansari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 28 - Number 11
Year of Publication: 2011
Authors: Deepak Singh, Vikas Singh, Uzma Ansari
10.5120/3428-4281

Deepak Singh, Vikas Singh, Uzma Ansari . Binary Particle Swarm Optimization with Crossover Operation for Discrete Optimization. International Journal of Computer Applications. 28, 11 ( August 2011), 19-24. DOI=10.5120/3428-4281

@article{ 10.5120/3428-4281,
author = { Deepak Singh, Vikas Singh, Uzma Ansari },
title = { Binary Particle Swarm Optimization with Crossover Operation for Discrete Optimization },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 28 },
number = { 11 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 19-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume28/number11/3428-4281/ },
doi = { 10.5120/3428-4281 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:14:31.164506+05:30
%A Deepak Singh
%A Vikas Singh
%A Uzma Ansari
%T Binary Particle Swarm Optimization with Crossover Operation for Discrete Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 28
%N 11
%P 19-24
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The field of discrete optimization consists of the areas of linear and integer programming, cover problems, knapsack problems, graph theory, network-flow problems, and scheduling. This paper performs an Experiment for discrete Optimization problem with the Hybridization of Binary Particle Swarm Optimization (BPSO) and Genetic Crossover. There are many algorithms Present for solving discrete optimization problem. Both BPSO and GA have shown to be very effective results. Experiment performed on this paper is for the analysis and behavioral study of Hybridized algorithm. We conclude with the results obtained by the performed experiment on standard benchmark functions, and it is found that proposed algorithm gives better results for few standard benchmark functions.

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Index Terms

Computer Science
Information Sciences

Keywords

Binary Particle Swarm Optimization BPSO Genetic Algorithm GA Hybrid Binary Particle Swarm Optimization HBPSO Crossover

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