Abdullahi Abubakar Mas’ud , Ahmed T. Salawudeen , Abubakar A. Umar , Yusuf A. Shaaban , Firdaus Muhammad-Sukki , Umar Musa , Saud J. Alshammari
{"title":"A QOBL-SAO and its variant: An open source software for optimizing PV/wind/battery system and CEC2020 real world problems","authors":"Abdullahi Abubakar Mas’ud , Ahmed T. Salawudeen , Abubakar A. Umar , Yusuf A. Shaaban , Firdaus Muhammad-Sukki , Umar Musa , Saud J. Alshammari","doi":"10.1016/j.simpa.2024.100630","DOIUrl":null,"url":null,"abstract":"<div><p>The Quasi oppositional smell agent optimization (QOBL-SAO) and its levy flight variant (LFQOBL-SAO) are two cutting-edge software tools for optimizing PV/wind/battery power systems. They can also be used to solve real-world CEC2020 optimization problems and are as good as top-performing software such as IUDE, <span><math><mi>ϵ</mi></math></span> MAgES and the iLSHAD <span><math><mi>ɛ</mi></math></span>. The QOBL-SAO exploits the random mode’s weakness and then adds a number to the initial population. The LFQOBL-SAO, on the other hand, improves the random mode’s weakness in order to solve this problem. The LFQOBL-SAO improves performance and search space by using levy flight instead of random code.</p></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665963824000186/pdfft?md5=34c0be540ac407437f5949fd3034bd29&pid=1-s2.0-S2665963824000186-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Impacts","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665963824000186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
The Quasi oppositional smell agent optimization (QOBL-SAO) and its levy flight variant (LFQOBL-SAO) are two cutting-edge software tools for optimizing PV/wind/battery power systems. They can also be used to solve real-world CEC2020 optimization problems and are as good as top-performing software such as IUDE, MAgES and the iLSHAD . The QOBL-SAO exploits the random mode’s weakness and then adds a number to the initial population. The LFQOBL-SAO, on the other hand, improves the random mode’s weakness in order to solve this problem. The LFQOBL-SAO improves performance and search space by using levy flight instead of random code.
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