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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
A comparative study of various meta-heuristic techniques applied to the multilevel thresholding problem
Engineering Applications of Artificial Intelligence, Volume 23, No. 5, Year 2010
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Description
The multilevel thresholding problem is often treated as a problem of optimization of an objective function. This paper presents both adaptation and comparison of six meta-heuristic techniques to solve the multilevel thresholding problem: a genetic algorithm, particle swarm optimization, differential evolution, ant colony, simulated annealing and tabu search. Experiments results show that the genetic algorithm, the particle swarm optimization and the differential evolution are much better in terms of precision, robustness and time convergence than the ant colony, simulated annealing and tabu search. Among the first three algorithms, the differential evolution is the most efficient with respect to the quality of the solution and the particle swarm optimization converges the most quickly. © 2009 Elsevier Ltd. All rights reserved.
Authors & Co-Authors
Hammouche, Kamal
Algeria, Tizi Ouzou
Université Mouloud Mammeri de Tizi Ouzou
Diaf, Moussa
Algeria, Tizi Ouzou
Université Mouloud Mammeri de Tizi Ouzou
Siarry, Patrick
France, Creteil
Université Paris-est Créteil Val de Marne
Statistics
Citations: 207
Authors: 3
Affiliations: 2
Identifiers
Doi:
10.1016/j.engappai.2009.09.011
ISSN:
09521976
Research Areas
Genetics And Genomics