A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems
Joint Authors
Liu, Wei
Liu, Fang
Chen, Hanning
Jing, Shikai
Liang, Xiaodan
Su, Weixing
Lin, Na
Source
Saudi Journal of Biological Sciences
Issue
Vol. 24, Issue 3 (31 Mar. 2017), pp.695-702, 8 p.
Publisher
Publication Date
2017-03-31
Country of Publication
Saudi Arabia
No. of Pages
8
Main Subjects
Topics
Abstract EN
There are many dynamic optimization problems in the real world, whose convergence and searching ability is cautiously desired, obviously different from static optimization cases.
This requires an optimization algorithm adaptively seek the changing optima over dynamic environments, instead of only finding the global optimal solution in the static environment.
This paper proposes a novel comprehensive learning artificial bee colony optimizer (CLABC) for optimization in dynamic environments problems, which employs a pool of optimal foraging strategies to balance the exploration and exploitation tradeoff.
The main motive of CLABC is to enrich artificial bee foraging behaviors in the ABC model by combining Powell’s pattern search method, life-cycle, and crossover-based social learning strategy.
The proposed CLABC is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs.
The experiments for evaluating CLABC are conducted on the dynamic moving peak benchmarks.
Furthermore, the proposed algorithm is applied to a realworld application of dynamic RFID network optimization.
Statistical analysis of all these cases highlights the significant performance improvement due to the beneficial combination and demonstrates the performance superiority of the proposed algorithm.
American Psychological Association (APA)
Chen, Hanning& Liu, Fang& Lin, Na& Jing, Shikai& Liang, Xiaodan& Liu, Wei…[et al.]. 2017. A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems. Saudi Journal of Biological Sciences،Vol. 24, no. 3, pp.695-702.
https://search.emarefa.net/detail/BIM-761804
Modern Language Association (MLA)
Lin, Na…[et al.]. A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems. Saudi Journal of Biological Sciences Vol. 24, no. 3 (Mar. 2017), pp.695-702.
https://search.emarefa.net/detail/BIM-761804
American Medical Association (AMA)
Chen, Hanning& Liu, Fang& Lin, Na& Jing, Shikai& Liang, Xiaodan& Liu, Wei…[et al.]. A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems. Saudi Journal of Biological Sciences. 2017. Vol. 24, no. 3, pp.695-702.
https://search.emarefa.net/detail/BIM-761804
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 702
Record ID
BIM-761804