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A Modified Hybrid Particle Swarm Optimization Algorithm for Multidimensional Knapsack Problem

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International Journal of Computer Applications
© 2011 by IJCA Journal
Volume 34 - Number 2
Year of Publication: 2011
Authors:
Said Labed
Amira Gherboudj
Salim Chikhi
10.5120/4070-5586

Said Labed, Amira Gherboudj and Salim Chikhi. Article: A Modified Hybrid Particle Swarm Optimization Algorithm for Multidimensional Knapsack Problem. International Journal of Computer Applications 34(2):11-16, November 2011. Full text available. BibTeX

@article{key:article,
	author = {Said Labed and Amira Gherboudj and Salim Chikhi},
	title = {Article: A Modified Hybrid Particle Swarm Optimization Algorithm for Multidimensional Knapsack Problem},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {34},
	number = {2},
	pages = {11-16},
	month = {November},
	note = {Full text available}
}

Abstract

In this paper, a modified hybrid Particle Swarm Optimization (MHPSO) algorithm that combines some principles of Particle Swarm Optimization (PSO) and Crossover operation of the Genetic Algorithm (GA) is presented. Our contribution has a twofold aim: first, is to propose a new hybrid PSO algorithm. Second is to prove the effectiveness of the proposed algorithm in dealing with NP-hard and combinatorial optimization problems. In order to test and validate our algorithm, we have used it for solving the Multidimensional Knapsack Problem (MKP) which is a NP-hard combinatorial optimization problem. The experimental results based on some benchmarks from OR-Library, show a good and promise solution quality obtained by the proposed algorithm.

Reference

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