{"title":"ALGORITMO GENÉTICO DE CHAVES ALEATÓRIAS VICIADAS ESPECIALIZADO PARA O PROBLEMA DE CORTE BIDIMENSIONAL NÃO GUILHOTINADO","authors":"Eliane Vendramini de Oliveira","doi":"10.5747/ce.2022.v14.e392","DOIUrl":null,"url":null,"abstract":"The Two-Dimensional Cutting Problem has a direct relationship with problems of industries. There are several proposals for solving this problem. In particular, solution proposals using metaheuristics were the focus of this research. Thus, in this paper we present a specialized genetic algorithm of randomized random keys. Several tests were performed using known instances in the specific literature, and the results found by the metaheuristic proposed were in many cases, equal or superior, to the results already published in the literature. Another comparative of results presented in this paper is related to the results obtained by the metaheuristic expert and results found by mathematical modeling using commercial software. In this case, again the genetic algorithm presented results equal to or very close to the optimum found by the mathematical model. In addition, the optimization proposal was extended to two-dimensional non-guillotine cut without parts orientation.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"161 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Colloquium Exactarum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5747/ce.2022.v14.e392","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
The Two-Dimensional Cutting Problem has a direct relationship with problems of industries. There are several proposals for solving this problem. In particular, solution proposals using metaheuristics were the focus of this research. Thus, in this paper we present a specialized genetic algorithm of randomized random keys. Several tests were performed using known instances in the specific literature, and the results found by the metaheuristic proposed were in many cases, equal or superior, to the results already published in the literature. Another comparative of results presented in this paper is related to the results obtained by the metaheuristic expert and results found by mathematical modeling using commercial software. In this case, again the genetic algorithm presented results equal to or very close to the optimum found by the mathematical model. In addition, the optimization proposal was extended to two-dimensional non-guillotine cut without parts orientation.