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Jia D, Li T, Zhang Y, Wang H. A Memetic Artificial Bee Colony Algorithm for High Dimensional Problems. INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS 2020. [DOI: 10.1142/s146902682050008x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
This work proposed a memetic version of Artificial Bee Colony algorithm, or called LSABC, which employed a “shrinking” local search strategy. By gradually shrinking the local search space along with the optimization process, the proposed LSABC algorithm randomly explores a large space in the early run time. This helps to avoid premature convergence. Then in the later evolution process, the LSABC finely exploits a small region around the current best solution to achieve a more accurate output value. The optimization behavior of the LSABC algorithm was studied and analyzed in the work. Compared with the classic ABC and several other state-of-the-art optimization algorithms, the LSABC shows a better performance in terms of convergence rate and quality of results for high-dimensional problems.
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Affiliation(s)
- Dongli Jia
- School of Information and Electronic Engineering, Hebei University of Engineering, GuangMing Street 199#, HanDan, HeBei 056001, China
| | - Teng Li
- School of Information and Electronic Engineering, Hebei University of Engineering, GuangMing Street 199#, HanDan, HeBei 056001, China
| | - Yufei Zhang
- School of Information and Electronic Engineering, Hebei University of Engineering, GuangMing Street 199#, HanDan, HeBei 056001, China
| | - Haijiang Wang
- School of Information and Electronic Engineering, Hebei University of Engineering, GuangMing Street 199#, HanDan, HeBei 056001, China
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