S. S. Biswal, D. Swain, P. Rout, Adyashree Das, Ajay K. Mishra
{"title":"A Comprehensive Review of Metaheuristic Algorithms Inspired by Quantum Mechanics","authors":"S. S. Biswal, D. Swain, P. Rout, Adyashree Das, Ajay K. Mishra","doi":"10.1109/APSIT58554.2023.10201716","DOIUrl":null,"url":null,"abstract":"This article comprehensively reviews the recently developed quantum mechanics-based optimization techniques. The quantum theory has been employed to speed up the evolutionary method and enhance the possibility of finding the optimal solution of conventional optimization techniques. Current developments in quantum computing have demonstrated that quantum theory can offer significant benefits over conventional theory for certain optimization techniques. The future prospective and benefits and drawbacks of this fresh category of quantum optimization techniques have been presented in this review. It also enables new researchers and algorithm developers to use these simple but extremely effective algorithms for problem-solving. This paper aims to give readers an overview of the fundamental elements and recent advances in optimization techniques so that they can develop and implement these for various applications. Finally, a few findings are reached, and future study on quantum-based optimization techniques is discussed.","PeriodicalId":170044,"journal":{"name":"2023 International Conference in Advances in Power, Signal, and Information Technology (APSIT)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference in Advances in Power, Signal, and Information Technology (APSIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIT58554.2023.10201716","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
This article comprehensively reviews the recently developed quantum mechanics-based optimization techniques. The quantum theory has been employed to speed up the evolutionary method and enhance the possibility of finding the optimal solution of conventional optimization techniques. Current developments in quantum computing have demonstrated that quantum theory can offer significant benefits over conventional theory for certain optimization techniques. The future prospective and benefits and drawbacks of this fresh category of quantum optimization techniques have been presented in this review. It also enables new researchers and algorithm developers to use these simple but extremely effective algorithms for problem-solving. This paper aims to give readers an overview of the fundamental elements and recent advances in optimization techniques so that they can develop and implement these for various applications. Finally, a few findings are reached, and future study on quantum-based optimization techniques is discussed.