{"title":"CONTOPT-JS: Metaheuristic Algorithms based JavaScript Software Library for Continuous Optimization Problems","authors":"O. Gokalp, Aybars Uğur, Sema Bodur","doi":"10.54856/jiswa.201905050","DOIUrl":null,"url":null,"abstract":"In this study, a software library called CONTOPT-JS has been developed for solving continuous optimization problems. By using this JavaScript language based library, fully client-side web applications can be developed. In the library, Artificial Bee Colony, Differential Evolution, Particle Swarm Optimization and Evolution Strategies metaheuristics exist and new algorithms and new problems can be added because of its modular design. Using the CONTOPT-JS library, experimental works have been conducted on some standard optimization benchmark functions and Sensor Deployment application area and the obtained results have been presented.","PeriodicalId":112412,"journal":{"name":"Journal of Intelligent Systems with Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent Systems with Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54856/jiswa.201905050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, a software library called CONTOPT-JS has been developed for solving continuous optimization problems. By using this JavaScript language based library, fully client-side web applications can be developed. In the library, Artificial Bee Colony, Differential Evolution, Particle Swarm Optimization and Evolution Strategies metaheuristics exist and new algorithms and new problems can be added because of its modular design. Using the CONTOPT-JS library, experimental works have been conducted on some standard optimization benchmark functions and Sensor Deployment application area and the obtained results have been presented.