Open AccessPiecewise Linear map enabled Harris Hawk optimization algorithm
Author(s) -
Juan Zhao,
Zheng-Ming Gao,
Yu-Jun Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1994/1/012038
Subject(s) - randomness , chaotic , algorithm , piecewise linear function , chaotic map , piecewise , computer science , chaos (operating system) , mathematical optimization , monte carlo method , optimization algorithm , mathematics , artificial intelligence , statistics , mathematical analysis , geometry , computer security
Chaotic maps were usually introduced to improve the original swarm-based nature-inspired algorithms. Due to their chaotic characteristics, the chaotic maps were introduced to replace the pseudo random numbers in computer engineering and consequently better performance would be achieved. In this paper, we introduce another chaotic improvement to the Harris hawk optimization (HHO) algorithm with Piecewise Linear map. Nevertheless, the chaos would be introduced to improve the randomness of the controlling parameter which was used to balance the ratio of exploration and exploitation. Monte Carlo simulation experiments were carried out and results confirmed this kind of improvements would significantly raise the capability in optimization.;