{"title":"Optimization algorithm based on niche genetic algorithm for irregular nesting problem","authors":"L. Haiming, Zhou Jiong, Wu Xinsheng, Lu Jiaxiang","doi":"10.1109/CCDC.2015.7162678","DOIUrl":null,"url":null,"abstract":"This paper presents an improved genetic algorithm based on niche strategy to solve the irregular nesting problem, which exists widely in modern manufacturing industry. For the niche strategy used in genetic algorithm, exclusion mechanism is introduced to avoid too many solutions with high similarity in the population, guaranteeing diversity of the solution set and preventing premature convergence of genetic search. No-fit polygon method based on Bottom-left strategy is used to evaluate the best placement position for every irregular part. Computational experiments based on data set published in the literature are taken to verify feasibility and effectiveness of the algorithm. The experiment results show that the proposed algorithm can be used to solve the nesting problem and generates some better solutions than the solutions published solutions for most examples.","PeriodicalId":273292,"journal":{"name":"The 27th Chinese Control and Decision Conference (2015 CCDC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 27th Chinese Control and Decision Conference (2015 CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2015.7162678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents an improved genetic algorithm based on niche strategy to solve the irregular nesting problem, which exists widely in modern manufacturing industry. For the niche strategy used in genetic algorithm, exclusion mechanism is introduced to avoid too many solutions with high similarity in the population, guaranteeing diversity of the solution set and preventing premature convergence of genetic search. No-fit polygon method based on Bottom-left strategy is used to evaluate the best placement position for every irregular part. Computational experiments based on data set published in the literature are taken to verify feasibility and effectiveness of the algorithm. The experiment results show that the proposed algorithm can be used to solve the nesting problem and generates some better solutions than the solutions published solutions for most examples.