Past five years on strategies and applications in hybrid brain storm optimization algorithms: a review

Author:

Simić Dragan1ORCID,Banković Zorana2,Villar José R3ORCID,Calvo-Rolle José Luis4ORCID,Ilin Vladimir5ORCID,Simić Svetislav D6ORCID,Simić Svetlana7ORCID

Affiliation:

1. University of Novi Sad , Faculty of Technical Sciences, Trg Dositeja Obradovića 6, 21000 Novi Sad, Serbia , dsimic@eunet.rs

2. Frontiers Media SA , Paseo de Castellana 77, 28046 Madrid, Spain , zbankovic@gmail.com

3. University of Oviedo , Computer Science Department, Campus de Llamaquique, 33005 Oviedo, Spain , villarjose@uniovi.es

4. University of A Coruña , Department of Industrial Engineering, 15405 Ferrol-A Coruña, Spain , jlcalvo@udc.es

5. University of Novi Sad , Faculty of Technical Sciences, Trg Dositeja Obradovića 6, 21000 Novi Sad, Serbia , v.ilin@uns.ac.rs

6. University of Novi Sad , Faculty of Technical Sciences, Trg Dositeja Obradovića 6, 21000 Novi Sad, Serbia , simicsvetislav@uns.ac.rs

7. University of Novi Sad , Faculty of Medicine, Hajduk Veljkova 1–9, 21000 Novi Sad, Serbia , svetlana.simic@mf.uns.ac.rs

Abstract

Abstract Optimization, in general, is regarded as the process of finding optimal values for the variables of a given problem in order to minimize or maximize one or more objective function(s). Brain storm optimization (BSO) algorithm solves a complex optimization problem by mimicking the human idea generating process, in which a group of people solves a problem together. The aim of this paper is to present hybrid BSO algorithm solutions in the past 5 years. This study could be divided into two parts: strategies and applications. In the first part, different strategies for the hybrid BSO algorithms intended to improve the various ability of the original BSO algorithm are displayed. In the second part, the real-world applications in the past five years in optimization, prediction and feature selection processes are presented.

Publisher

Oxford University Press (OUP)

Reference83 articles.

1. Brain storm optimization for electromagnetic applications: continuous and discrete;Aldhafeeri;IEEE Transactions on Antennas and Propagation,2019

2. R.M.A. Hybrid brain storm optimization algorithm and late acceptance hill climbing to solve the flexible job-shop scheduling problem;Alzaqebah;J. of King Saud University – Computer and Information Sciences,2022

3. Heap-based optimizer inspired by corporate rank hierarchy for global optimization;Askari;Expert Systems with Applications. Vol.,2020

4. Political optimizer: a novel socio-inspired meta-heuristic for global optimization;Askari;Knowledge-Based Systems. Vol.,2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3