{"title":"Laminated plate design using genetic algorithms and parallel processing","authors":"Joseph Lynn Henderson","doi":"10.1016/0956-0521(94)90025-6","DOIUrl":null,"url":null,"abstract":"<div><p>The use of a parallel computer in the stacking sequence optimization of a composite laminate via a genetic algorithm is studied. Results are obtained for a graphite-epoxy plate under buckling, strain, and ply contiguity constraints. Two parallelization schemes for the optimization problem are proposed and compared. Results are presented showing the computation time as a function of the number of processors, illustrating the benefits and drawbacks of both schemes. A new technique for design population visualization is also developed as a tool for monitoring the performance of the genetic algorithm.</p></div>","PeriodicalId":100325,"journal":{"name":"Computing Systems in Engineering","volume":"5 4","pages":"Pages 441-453"},"PeriodicalIF":0.0000,"publicationDate":"1994-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0956-0521(94)90025-6","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computing Systems in Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0956052194900256","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
The use of a parallel computer in the stacking sequence optimization of a composite laminate via a genetic algorithm is studied. Results are obtained for a graphite-epoxy plate under buckling, strain, and ply contiguity constraints. Two parallelization schemes for the optimization problem are proposed and compared. Results are presented showing the computation time as a function of the number of processors, illustrating the benefits and drawbacks of both schemes. A new technique for design population visualization is also developed as a tool for monitoring the performance of the genetic algorithm.