Abstract
The harmony search algorithm (HSA) is one of the most widely used meta-heuristic optimization algorithms. During the last two decades, many improved versions and variants of HSA have been proposed to improve the algorithms efficiency and usability. In this study, a HSA variant with unique structural characteristics is proposed, named multi-layered harmony search algorithm (MLHSA). The multi-layered structure is specifically designed for the effective improvement of exploration and exploitation capability. The proposed MLHSA is applied to a set of benchmark problems to test and verify the efficiency. The application results show that MLHSA outperforms other meta-heuristic algorithms, indicating the competitiveness of the algorithm. The multi-layer concept can be easily employed to other algorithms, as a helpful tool for the improvement of existing algorithms convergence.
Original language | English |
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Title of host publication | Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) |
Editors | Javier Del Ser |
Publisher | Springer Verlag |
Pages | 8-14 |
Number of pages | 7 |
ISBN (Print) | 9789811037276 |
DOIs | |
Publication status | Published - 2017 |
Event | Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 - Bilbao, Spain Duration: 2017 Feb 22 → 2017 Feb 24 |
Publication series
Name | Advances in Intelligent Systems and Computing |
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Volume | 514 |
ISSN (Print) | 2194-5357 |
Other
Other | Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 |
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Country/Territory | Spain |
City | Bilbao |
Period | 17/2/22 → 17/2/24 |
Bibliographical note
Funding Information:This research was supported by a grant from The National Research Foundation (NRF) of Korea, funded by the Korean government (MSIP) under no. 2016R1A2A1A05005306.
Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2017.
Keywords
- Harmony search algorithm
- Meta-heuristic
- Multi-layered harmony search algorithm
- Optimization
ASJC Scopus subject areas
- Control and Systems Engineering
- General Computer Science