1P-ABC, a Simpli ed ABC Variant for Continuous Optimization Problems
Journal Title: Journal of Advances in Mathematics and Computer Science - Year 2017, Vol 25, Issue 5
Abstract
In this paper a novel simpli ed and fast variant of the ABC algorithm is proposed, 1 Population ABC (1P-ABC), with the aim to increase the eciency of the ABC algorithm by using only one population of bees, the employed bees, while maintaining a good e ectiveness of the algorithm in solving dicult nonlinear optimization problems. The novel 1P-ABC algorithm was tested, both regarding the eciency and the success rate, against three known variants of ABC, the original ABC algorithm, an improved variant, Gbest-guided Arti cial Bee Colony (GABC), and another improved variant, Fast ABC (F-ABC). The testing was conducted by employing an original testing methodology over a set of 11 scalable, multimodal, continuous optimization functions (10 unconstrained and 1 constrained) most of them with known global solutions. The novel proposed 1P-ABC algorithm outperformed the other ABC variants in eciency, while for the success rate the results were mixed.
Authors and Affiliations
George Anescu
Keywords
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- EP ID EP322420
- DOI 10.9734/JAMCS/2017/38065
- Views 71
- Downloads 0
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