Hybrid artificial bee colony algorithm and particle swarm search for global optimization
type: Item
instance of: scholarly article
title: Hybrid artificial bee colony algorithm and particle swarm search for global optimization
zbMATH Open document ID: 1407.90373
DOI: 10.1155/2014/832949
author: Chunfeng Wang
author: Kui Liu
author: Peiping Shen
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: Artificial bee colony (ABC) algorithm is one of the most recent swarm intelligence based algorithms, which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this problem, we propose a novel artificial bee colony algorithm based on particle swarm search mechanism. In this algorithm, for improving the convergence speed, the initial population is generated by using good point set theory rather than random selection firstly. Secondly, in order to enhance the exploitation ability, the employed bee, onlookers, and scouts utilize the mechanism of PSO to search new candidate solutions. Finally, for further improving the searching ability, the chaotic search operator is adopted in the best solution of the current iteration. Our algorithm is tested on some well-known benchmark functions and compared with other algorithms. Results show that our algorithm has good performance.
Mathematics Subject Classification ID: 90C59
Mathematics Subject Classification ID: 90C26
zbMATH DE Number: 7017385
Wikidata QID: Q59069796
describes a project that uses: ABC
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/832949
OpenAlex ID: W1986552887
cites work: Q5480099
cites work: A unified ant colony optimization algorithm for continuous optimization
cites work: A novel hybrid differential evolution and particle swarm optimization algorithm for unconstrained optimization
cites work: Gbest-guided artificial bee colony algorithm for numerical function optimization
cites work: A modified artificial bee colony algorithm based on converge-onlookers approach for global optimization
description: scientific article; zbMATH DE number 7017385