Parallel Implementation of Synchronous Type Artificial Bee Colony Algorithm for Global Optimization

Evolutionary algorithms often need huge running times when solving large-scale optimization problems. One of the solutions for this issue is to introduce parallelization into the algorithm. To benefit from this approach for the artificial bee colony optimization algorithm, we present a new synchrono...

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Vydáno v:Journal of optimization theory and applications Ročník 155; číslo 3; s. 1095 - 1104
Hlavní autoři: Basturk, Alper, Akay, Rustu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Boston Springer US 01.12.2012
Springer Nature B.V
Témata:
Algorithms
Applications of Mathematics
Calculus of Variations and Optimal Control; Optimization
Colonies
Communication
Computation
Engineering
Evolutionary algorithms
Experiments
Food
Foraging behavior
Genetic algorithms
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Optimization algorithms
Parallel processing
Performance evaluation
Population
Running
Studies
Synchronous
Theory of Computation
Parallel computing
Global optimization
Parallel algorithms
Artificial bee colony optimization algorithm
ISSN:0022-3239, 1573-2878
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Shrnutí:Evolutionary algorithms often need huge running times when solving large-scale optimization problems. One of the solutions for this issue is to introduce parallelization into the algorithm. To benefit from this approach for the artificial bee colony optimization algorithm, we present a new synchronous and parallel version of the algorithm. Performances of the proposed version and the original asynchronous algorithm are compared in terms of efficiency and speedup. Algorithms are competed to solve 20 large-scale global optimization problems. Comparative results show that the proposed parallel algorithm is still efficient as asynchronous version while it requires much less time to solve complex and large problems.
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ISSN:0022-3239
1573-2878
DOI:10.1007/s10957-012-0107-5