Adaptive Relative Reflection Harris Hawks Optimization for Global Optimization

Tingting Zou and Changyu Wang
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Tingting Zou: Information Science and Technology College, Dalian Maritime University, Dalian 116026, China
Changyu Wang: Information Science and Technology College, Dalian Maritime University, Dalian 116026, China

Mathematics, 2022, vol. 10, issue 7, 1-19

Abstract: The Harris Hawks optimization (HHO) is a population-based metaheuristic algorithm; however, it has low diversity and premature convergence in certain problems. This paper proposes an adaptive relative reflection HHO (ARHHO), which increases the diversity of standard HHO, alleviates the problem of stagnation of local optimal solutions, and improves the search accuracy of the algorithm. The main features of the algorithm define nonlinear escape energy and adaptive weights and combine adaptive relative reflection with the HHO algorithm. Furthermore, we prove the computational complexity of the ARHHO algorithm. Finally, the performance of our algorithm is evaluated by comparison with other well-known metaheuristic algorithms on 23 benchmark problems. Experimental results show that our algorithms performs better than the compared algorithms on most of the benchmark functions.

Keywords: Harris Hawks optimization; escape energy; adaptive relative reflection; computational complexity (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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