Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning
Most metaheuristic algorithms, including harmony search (HS), suffer from parameter selection. Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/25051/ http://umpir.ump.edu.my/id/eprint/25051/ http://umpir.ump.edu.my/id/eprint/25051/ http://umpir.ump.edu.my/id/eprint/25051/8/Hybrid%20Harmony%20Search%20Algorithm%20with%20Grey%20Wolf1.pdf |