Z. Arfeen, M. Abdullah, M. Shehzad, Saleh Altbawi, Muhammad Ashafaq Khan Jiskani, Muhammad Asif Imran YiRan
{"title":"A Niche Particle Swarm Optimization-Perks and Perspectives","authors":"Z. Arfeen, M. Abdullah, M. Shehzad, Saleh Altbawi, Muhammad Ashafaq Khan Jiskani, Muhammad Asif Imran YiRan","doi":"10.1109/ICSET51301.2020.9265384","DOIUrl":null,"url":null,"abstract":"Optimization is a method for searching the best candidate solution to lessen or expand the value of the objective problem. Broadly speaking algorithms can be orgabized into four main classes, i.e. biology-based algorithms, physics-based algorithms, sociology-based algorithms, and human intelligence-based algorithms. Swarm-intelligence (SI) based algorithms appeared as a commanding family of optimization techniques. The paper aims to commence a brief review of meta-heuristic algorithms especially Particle swarm optimization (PSO) and its sister variants in short. The understudy paper covers all important aspects of swarm intelligence PSO with deep insight learning for practitioners and scholars.","PeriodicalId":299530,"journal":{"name":"2020 IEEE 10th International Conference on System Engineering and Technology (ICSET)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 10th International Conference on System Engineering and Technology (ICSET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSET51301.2020.9265384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Optimization is a method for searching the best candidate solution to lessen or expand the value of the objective problem. Broadly speaking algorithms can be orgabized into four main classes, i.e. biology-based algorithms, physics-based algorithms, sociology-based algorithms, and human intelligence-based algorithms. Swarm-intelligence (SI) based algorithms appeared as a commanding family of optimization techniques. The paper aims to commence a brief review of meta-heuristic algorithms especially Particle swarm optimization (PSO) and its sister variants in short. The understudy paper covers all important aspects of swarm intelligence PSO with deep insight learning for practitioners and scholars.