{"title":"冠状病毒优化(CVO):一种受冠状病毒大流行启发的新型优化算法。","authors":"Alireza Salehan, Arash Deldari","doi":"10.1007/s11227-021-04100-z","DOIUrl":null,"url":null,"abstract":"<p><p>This research introduces a new probabilistic and meta-heuristic optimization approach inspired by the Corona virus pandemic. Corona is an infection that originates from an unknown animal virus, which is of three known types and COVID-19 has been rapidly spreading since late 2019. Based on the SIR model, the virus can easily transmit from one person to several, causing an epidemic over time. Considering the characteristics and behavior of this virus, the current paper presents an optimization algorithm called Corona virus optimization (CVO) which is feasible, effective, and applicable. A set of benchmark functions evaluates the performance of this algorithm for discrete and continuous problems by comparing the results with those of other well-known optimization algorithms. The CVO algorithm aims to find suitable solutions to application problems by solving several continuous mathematical functions as well as three continuous and discrete applications. Experimental results denote that the proposed optimization method has a credible, reasonable, and acceptable performance.</p>","PeriodicalId":50034,"journal":{"name":"Journal of Supercomputing","volume":"78 4","pages":"5712-5743"},"PeriodicalIF":2.5000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8489174/pdf/","citationCount":"4","resultStr":"{\"title\":\"Corona virus optimization (CVO): a novel optimization algorithm inspired from the Corona virus pandemic.\",\"authors\":\"Alireza Salehan, Arash Deldari\",\"doi\":\"10.1007/s11227-021-04100-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This research introduces a new probabilistic and meta-heuristic optimization approach inspired by the Corona virus pandemic. Corona is an infection that originates from an unknown animal virus, which is of three known types and COVID-19 has been rapidly spreading since late 2019. Based on the SIR model, the virus can easily transmit from one person to several, causing an epidemic over time. Considering the characteristics and behavior of this virus, the current paper presents an optimization algorithm called Corona virus optimization (CVO) which is feasible, effective, and applicable. A set of benchmark functions evaluates the performance of this algorithm for discrete and continuous problems by comparing the results with those of other well-known optimization algorithms. The CVO algorithm aims to find suitable solutions to application problems by solving several continuous mathematical functions as well as three continuous and discrete applications. Experimental results denote that the proposed optimization method has a credible, reasonable, and acceptable performance.</p>\",\"PeriodicalId\":50034,\"journal\":{\"name\":\"Journal of Supercomputing\",\"volume\":\"78 4\",\"pages\":\"5712-5743\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8489174/pdf/\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Supercomputing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s11227-021-04100-z\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/10/4 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Supercomputing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s11227-021-04100-z","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/10/4 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Corona virus optimization (CVO): a novel optimization algorithm inspired from the Corona virus pandemic.
This research introduces a new probabilistic and meta-heuristic optimization approach inspired by the Corona virus pandemic. Corona is an infection that originates from an unknown animal virus, which is of three known types and COVID-19 has been rapidly spreading since late 2019. Based on the SIR model, the virus can easily transmit from one person to several, causing an epidemic over time. Considering the characteristics and behavior of this virus, the current paper presents an optimization algorithm called Corona virus optimization (CVO) which is feasible, effective, and applicable. A set of benchmark functions evaluates the performance of this algorithm for discrete and continuous problems by comparing the results with those of other well-known optimization algorithms. The CVO algorithm aims to find suitable solutions to application problems by solving several continuous mathematical functions as well as three continuous and discrete applications. Experimental results denote that the proposed optimization method has a credible, reasonable, and acceptable performance.
期刊介绍:
The Journal of Supercomputing publishes papers on the technology, architecture and systems, algorithms, languages and programs, performance measures and methods, and applications of all aspects of Supercomputing. Tutorial and survey papers are intended for workers and students in the fields associated with and employing advanced computer systems. The journal also publishes letters to the editor, especially in areas relating to policy, succinct statements of paradoxes, intuitively puzzling results, partial results and real needs.
Published theoretical and practical papers are advanced, in-depth treatments describing new developments and new ideas. Each includes an introduction summarizing prior, directly pertinent work that is useful for the reader to understand, in order to appreciate the advances being described.