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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Bibliographic Details
Published in:Symmetry (Basel) Vol. 14; no. 5; p. 967
Main Authors: Yan, Zhicheng, Jin, Qibing, Zhang, Yang, Wang, Zeyu, Li, Ziming
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.05.2022
Subjects:
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
Online Access:Get full text
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Summary: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.
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content type line 14
ISSN:2073-8994
2073-8994
DOI:10.3390/sym14050967