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Publication
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| Title of Article |
A Modified Artificial Bee Colony Algorithm with Firefly Algorithm Strategy for Continuous Optimization Problems |
| Date of Acceptance |
3 December 2018 |
| Journal |
| Title of Journal |
Journal of Applied Mathematics |
| Standard |
SCOPUS |
| Institute of Journal |
Hindawi |
| ISBN/ISSN |
1687-0042 |
| Volume |
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| Issue |
2018 |
| Month |
December |
| Year of Publication |
2020 |
| Page |
1-9 |
| Abstract |
Artifcial Bee Colony (ABC) algorithm is one of the efcient nature-inspired optimization algorithms for solving continuous problems. It has no sensitive control parameters and has been shown to be competitive with other well-known algorithms. However, the slow convergence, premature convergence, and being trapped within the local solutions may occur during the search. In this
paper, we propose a new Modifed Artifcial Bee Colony (MABC) algorithm to overcome these problems. All phases of ABC are determined for improving the exploration and exploitation processes.We use a new search equation in employed bee phase, increase the probabilities for onlooker bees to fnd better positions, and replace some worst positions by the new ones in onlooker bee phase. Moreover, we use the Firefy algorithm strategy to generate a new position replacing an unupdated position in scout bee phase. Its
performance is tested on selected benchmark functions. Experimental results show that MABC is more efective than ABC and some other modifcations of ABC. |
| Keyword |
optimization, nature-inspired optimization algorithms, Artifcial Bee Colony (ABC) algorithm |
| Author |
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| Reviewing Status |
มีผู้ประเมินอิสระ |
| Status |
ได้รับการตอบรับให้ตีพิมพ์ |
| Level of Publication |
นานาชาติ |
| citation |
true |
| Part of thesis |
true |
| Attach file |
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| Citation |
0
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Journal Publication
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