Murali Krishna Madugula, Santosh Kumar Majhi, Nibedan Panda
{"title":"An Efficient Arithmetic Optimization Algorithm for Solving Subset-sum Problem","authors":"Murali Krishna Madugula, Santosh Kumar Majhi, Nibedan Panda","doi":"10.1109/CSI54720.2022.9923996","DOIUrl":null,"url":null,"abstract":"The Subset-Sum Problem (SSP) ensures a significant role in various practical applications, which include cryptography and coding theory owing to the importance in the functionality of some of the public key cryptography systems. Consider the set S of n real numbers, where the 2n - 1 diverse subsets are presented without including the empty set. The SSP is defined as the determination of N subsets, where the summation of elements in the subset needs to be N the smallest over all the possible subsets. This problem was involved in diverse applications in operations research and practice. But, the problem is very complex in computation. Hence, this paper aims to solve the SSP with a well-enabled meta-heuristic algorithm named Arithmetic Optimization Algorithm (AOA). Here, a novel optimization algorithm is developed for reducing the error among the target and attained a solution, and also to solve the SSA issue. At last, the simulation analysis reveals that the suggested AOA can ensure optimal results when using the benchmark data.","PeriodicalId":221137,"journal":{"name":"2022 International Conference on Connected Systems & Intelligence (CSI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Connected Systems & Intelligence (CSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSI54720.2022.9923996","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The Subset-Sum Problem (SSP) ensures a significant role in various practical applications, which include cryptography and coding theory owing to the importance in the functionality of some of the public key cryptography systems. Consider the set S of n real numbers, where the 2n - 1 diverse subsets are presented without including the empty set. The SSP is defined as the determination of N subsets, where the summation of elements in the subset needs to be N the smallest over all the possible subsets. This problem was involved in diverse applications in operations research and practice. But, the problem is very complex in computation. Hence, this paper aims to solve the SSP with a well-enabled meta-heuristic algorithm named Arithmetic Optimization Algorithm (AOA). Here, a novel optimization algorithm is developed for reducing the error among the target and attained a solution, and also to solve the SSA issue. At last, the simulation analysis reveals that the suggested AOA can ensure optimal results when using the benchmark data.