An Improved Multi-Objective Harris Hawk Optimization with Blank Angle Region Enhanced Search

Aiming at the problems of low precision, low search efficiency, and being easy to fall into local optimization of the multi-objective harris hawk optimization algorithm (MOHHO) based on grid method, a MOHHO based on blank angle region enhanced search (BARESMOHHO) is proposed. The main changes of the...

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Vydané v:	Symmetry (Basel) Ročník 14; číslo 5; s. 967
Hlavní autori:	Yan, Zhicheng, Jin, Qibing, Zhang, Yang, Wang, Zeyu, Li, Ziming
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.05.2022
Predmet:	Algorithms Archives & records Decomposition Feature selection Genetic algorithms Grid method Heuristic Local optimization Mathematical programming Multiple objective analysis Optimization algorithms Population Searching Segmentation
ISSN:	2073-8994, 2073-8994
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Abstract	Aiming at the problems of low precision, low search efficiency, and being easy to fall into local optimization of the multi-objective harris hawk optimization algorithm (MOHHO) based on grid method, a MOHHO based on blank angle region enhanced search (BARESMOHHO) is proposed. The main changes of the algorithm are as follows: firstly, chaotic mapping is used to initialize the population, which is beneficial to speed up the search. Then, in order to find low-density regions faster, the algorithm adjusts the classification level according to the number of individuals in the external archive. In order to make the distribution of individuals in the target space more uniform, inspired by the idea of symmetrical segmentation, the number of archives at different levels are symmetrically distributed. Finally, it strengthens the search for the non-individual region (blank angle region) in the process of division. The effectiveness of the proposed algorithm is verified by comparing it with some known classical functions on test functions.
AbstractList	Aiming at the problems of low precision, low search efficiency, and being easy to fall into local optimization of the multi-objective harris hawk optimization algorithm (MOHHO) based on grid method, a MOHHO based on blank angle region enhanced search (BARESMOHHO) is proposed. The main changes of the algorithm are as follows: firstly, chaotic mapping is used to initialize the population, which is beneficial to speed up the search. Then, in order to find low-density regions faster, the algorithm adjusts the classification level according to the number of individuals in the external archive. In order to make the distribution of individuals in the target space more uniform, inspired by the idea of symmetrical segmentation, the number of archives at different levels are symmetrically distributed. Finally, it strengthens the search for the non-individual region (blank angle region) in the process of division. The effectiveness of the proposed algorithm is verified by comparing it with some known classical functions on test functions.
Author	Zhang, Yang Yan, Zhicheng Li, Ziming Jin, Qibing Wang, Zeyu
Author_xml	– sequence: 1 givenname: Zhicheng orcidid: 0000-0003-2893-4270 surname: Yan fullname: Yan, Zhicheng – sequence: 2 givenname: Qibing surname: Jin fullname: Jin, Qibing – sequence: 3 givenname: Yang surname: Zhang fullname: Zhang, Yang – sequence: 4 givenname: Zeyu surname: Wang fullname: Wang, Zeyu – sequence: 5 givenname: Ziming surname: Li fullname: Li, Ziming
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SubjectTerms	Algorithms Archives & records Decomposition Feature selection Genetic algorithms Grid method Heuristic Local optimization Mathematical programming Multiple objective analysis Optimization algorithms Population Searching Segmentation
Title	An Improved Multi-Objective Harris Hawk Optimization with Blank Angle Region Enhanced Search
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