On Modification and Application of the Artificial Bee Colony Algorithm
2
조회
0
다운로드
2
인용
0
참고문헌
키워드
초록
Artificial bee colony (ABC) algorithm has attracted significant interests recently for solving the multivariateoptimization problem. However, it still faces insufficiency of slow convergence speed and poor local searchability. Therefore, in this paper, a modified ABC algorithm with bees’ number reallocation and new searchequation is proposed to tackle this drawback. In particular, to enhance solution accuracy, more bees in thepopulation are assigned to execute local searches around food sources. Moreover, elite vectors are adopted toguide the bees, with which the algorithm could converge to the potential global optimal position rapidly. Aseries of classical benchmark functions for frequency-modulated sound waves are adopted to validate theperformance of the modified ABC algorithm. Experimental results are provided to show the significantperformance improvement of our proposed algorithm over the traditional version.
Abstract
Artificial bee colony (ABC) algorithm has attracted significant interests recently for solving the multivariateoptimization problem. However, it still faces insufficiency of slow convergence speed and poor local searchability. Therefore, in this paper, a modified ABC algorithm with bees’ number reallocation and new searchequation is proposed to tackle this drawback. In particular, to enhance solution accuracy, more bees in thepopulation are assigned to execute local searches around food sources. Moreover, elite vectors are adopted toguide the bees, with which the algorithm could converge to the potential global optimal position rapidly. Aseries of classical benchmark functions for frequency-modulated sound waves are adopted to validate theperformance of the modified ABC algorithm. Experimental results are provided to show the significantperformance improvement of our proposed algorithm over the traditional version.
참고문헌 (8)
- Y. Nie, "Homography propagation and optimization for widebaseline street image interpolation", IEEE Transactions on Visualization and Computer Graphics, 23(10), pp.2328~2341 (2017)[DOI]
- A. Sizov, "Direct optimization of the detection cost for I-vector-based spoken language recognition", IEEE, 2017, pp.25(3), 588~597
- S. Jiang, "A two-phase soft optimization method for the uncertain scheduling problem in the steelmaking industry", IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(3), pp.416~431 (2017)[DOI]
- W. Wu, "Robust secure beamforming for wireless powered full-duplex systems with self-energy recycling", IEEE Transactions on Vehicular Technology, 66(11), pp.10055~10069 (2017)[DOI]
- W. Wu, "Efficient transmission solutions for MIMO wiretap channels with SWIPT", IEEE Communications Letters, 19(9), pp.1548~1551 (2015)[DOI]
- M. S. Kiran, "A directed artificial bee colony algorithm", Applied Soft Computing, 26, pp.454~462 (2015)[DOI]
- I. Babaoglu, "Artificial bee colony algorithm with distribution-based update rule", Applied Soft Computing, 34, pp.851~861 (2015)[DOI]
- Y. Shi, "An improved artificial bee colony and its application", KnowledgeBased Systems, 107, pp.14~31 (2016)