Mine blast harmony search: A new hybrid optimization method for improving exploration and exploitation capabilities
- Authors
- Sadollah, Ali; Sayyaadi, Hassan; Yoo, Do Guen; Lee, Ho Min; Kim, Joong Hoon
- Issue Date
- Jul-2018
- Publisher
- ELSEVIER
- Keywords
- Harmony search; Mine blast algorithm; Hybrid metaheuristic methods; Global optimization; Large-scale problems
- Citation
- APPLIED SOFT COMPUTING, v.68, pp.548 - 564
- Indexed
- SCIE
SCOPUS
- Journal Title
- APPLIED SOFT COMPUTING
- Volume
- 68
- Start Page
- 548
- End Page
- 564
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/74399
- DOI
- 10.1016/j.asoc.2018.04.010
- ISSN
- 1568-4946
- Abstract
- This paper proposes a hybrid optimization method that combines the power of the harmony search (HS) with the mine blast algorithm (MBA). The resulting mine blast harmony search (MBHS) uses MBA for exploration and HS for exploitation. The HS is inspired by the improvisation process of musicians, while the MBA is derived based on explosion of landmines. The HS used in the hybrid algorithm is an improved version, introducing a new concept for the harmony memory size, while the MBA is modified in terms of its mathematical formulation. Several numerical problems and benchmarks with many design variables and constraints are used to validate MBHS, and the optimization results are compared with those from various algorithms in the literature. The numerical results show that the proposed hybrid method provides better exploitation ability (especially in the final iterations) and enjoys mature convergence to the optimum solution. (C) 2018 Elsevier B.V. All rights reserved.
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Collections - College of Engineering > School of Civil, Environmental and Architectural Engineering > 1. Journal Articles
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