Improved Bat Algorithm Based on Multipopulation Strategy of Island Model for Solving Global Function Optimization Problem. (18th August 2019)
- Record Type:
- Journal Article
- Title:
- Improved Bat Algorithm Based on Multipopulation Strategy of Island Model for Solving Global Function Optimization Problem. (18th August 2019)
- Main Title:
- Improved Bat Algorithm Based on Multipopulation Strategy of Island Model for Solving Global Function Optimization Problem
- Authors:
- Guo, Sha-Sha
Wang, Jie-Sheng
Ma, Xiao-Xu - Other Names:
- Alonso-Betanzos Amparo Academic Editor.
- Abstract:
- Abstract : The bat algorithm (BA) is a heuristic algorithm that globally optimizes by simulating the bat echolocation behavior. In order to improve the search performance and further improve the convergence speed and optimization precision of the bat algorithm, an improved algorithm based on chaotic map is introduced, and the improved bat algorithm of Levy flight search strategy and contraction factor is proposed. The optimal chaotic map operator is selected based on the simulation experiments results. Then, a multipopulation parallel bat algorithm based on the island model is proposed. Finally, the typical test functions are used to carry out the simulation experiments. The simulation results show that the proposed improved algorithm can effectively improve the convergence speed and optimization accuracy.
- Is Part Of:
- Computational intelligence and neuroscience. Volume 2019(2019)
- Journal:
- Computational intelligence and neuroscience
- Issue:
- Volume 2019(2019)
- Issue Display:
- Volume 2019, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 2019
- Issue:
- 2019
- Issue Sort Value:
- 2019-2019-2019-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-08-18
- Subjects:
- Neurosciences -- Data processing -- Periodicals
Computational intelligence -- Periodicals
Computational neuroscience -- Periodicals
612.80285 - Journal URLs:
- https://www.hindawi.com/journals/cin/ ↗
- DOI:
- 10.1155/2019/6068743 ↗
- Languages:
- English
- ISSNs:
- 1687-5265
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 11973.xml