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A Multi-Restart Dynamic Harris Hawk Optimization Algorithm for the Economic Load Dispatch Problem
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DOI：10.1109/ACCESS.2021.3109575.png)
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Abstract
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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.
Keywords:
Fuels
Heuristic algorithms
Cost function
Optimization
Costs
Rabbits
Mathematical model
Economic load dispatch problem
Harris Hawks optimization
multi-restart
opposition-based learning
Journal
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3.6
Papers:
9.8W
Citations:
29.4W
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