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New Particle Swarm Optimization algorithm for knapsack problem.

Authors :
Ouyang, Ling
Dongyun Wang
Source :
2012 8th International Conference on Natural Computation; 1/ 1/2012, p786-788, 3p
Publication Year :
2012

Abstract

In this paper it proposes an improved Particle Swarm Optimization (PSO) algorithm for the knapsack problem. The new algorithm is based on the standard PSO algorithm for overcoming the shortcomings that standard PSO traps into local optima easily and has a low convergence accuracy. When the load-bearing quantity of the knapsack is exceeded, the fitness will be sit zero. When the best position of the individual particle is the same with the best position of the population, the particle's position will be reinitialized. The simulation shows that the improved algorithm is simple and effective to solve the small-scale knapsack problem. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISBNs :
9781457721304
Database :
Complementary Index
Journal :
2012 8th International Conference on Natural Computation
Publication Type :
Conference
Accession number :
86517201
Full Text :
https://doi.org/10.1109/ICNC.2012.6234615