A Multi-Restart Dynamic Harris Hawk Optimization Algorithm for the Economic Load Dispatch Problem

In this study, we propose an algorithm based on a recently proposed metaheuristic called the Harris Hawk Optimization (HHO). We utilized a dynamic control strategy to enhance the exploration capability. To further avoid trapping in local optima, we incorporate opposition-based learning (OLB) and a m...

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Veröffentlicht in:IEEE access Jg. 9; S. 122180 - 122206
Hauptverfasser: Pham, Tan Nhat, Tran, Ly Van, Dao, Son Vu Truong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Cost function
Costs
Dynamic control
Economic load dispatch problem
Fuels
Harris Hawks optimization
Heuristic algorithms
Heuristic methods
Machine learning
Mathematical model
multi-restart
opposition-based learning
Optimization
Rabbits
Strategy
ISSN:2169-3536, 2169-3536
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Zusammenfassung:In this study, we propose an algorithm based on a recently proposed metaheuristic called the Harris Hawk Optimization (HHO). We utilized a dynamic control strategy to enhance the exploration capability. To further avoid trapping in local optima, we incorporate opposition-based learning (OLB) and a multi-restart strategy. The proposed algorithm is used to solve economic load dispatch (ELD) problems with non-smooth cost functions. The ELD problems have a very large search space and therefore it is difficult to find global optimum using analytical methods. The results of the proposed approach are very competitive compared with notable results from previous research.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3109575