Chih-Cheng Chang, Chi-Yuan Chen, Cheng-Wei Fan, H. Chao, Yao-Hsin Chou
{"title":"Quantum-Inspired Electromagnetism-Like Mechanism for Solving 0/1 Knapsack Problem","authors":"Chih-Cheng Chang, Chi-Yuan Chen, Cheng-Wei Fan, H. Chao, Yao-Hsin Chou","doi":"10.1109/ITCS.2010.5581278","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a novel evolutionary computing method which is called quantum-inspired electromagnetism-like mechanism (QEM) to solve 0/1 knapsack problem. QEM is based on the electromagnetism theory and using the characteristic of quantum computing. It can rapidly and efficiently find out the optimal solution of combination optimization problem. We compare the conventional genetic algorithm (CGA), quantum-inspired genetic algorithm (QGA), quantum-inspired electromagnetism-like mechanism algorithm (QEM). The experiment results show that the QEM is better than CGA, EM and QGA in general cases.","PeriodicalId":166169,"journal":{"name":"2010 2nd International Conference on Information Technology Convergence and Services","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Conference on Information Technology Convergence and Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITCS.2010.5581278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, we propose a novel evolutionary computing method which is called quantum-inspired electromagnetism-like mechanism (QEM) to solve 0/1 knapsack problem. QEM is based on the electromagnetism theory and using the characteristic of quantum computing. It can rapidly and efficiently find out the optimal solution of combination optimization problem. We compare the conventional genetic algorithm (CGA), quantum-inspired genetic algorithm (QGA), quantum-inspired electromagnetism-like mechanism algorithm (QEM). The experiment results show that the QEM is better than CGA, EM and QGA in general cases.