{"title":"Application of Adaptive Genetic Algorithm in Optimal Scheduling of Aviation Materials","authors":"J. Shang","doi":"10.1155/2022/1467935","DOIUrl":null,"url":null,"abstract":"The maintenance and logistics support of aircraft are critical to the flight safety. The configuration and scheduling of air materials are the basis of maintenance and logistics. This research establishes the model of air material scheduling problem and introduces NSGA-II genetic algorithm with adaptive design to optimize the air material scheduling arrangement. This adaptive design improves the local optimal solution problem of NSGA-II and makes the optimal scheduling of air materials more accurate. In some cases, the improved NSGA-II algorithm is expressed to zero deviation, which is not achieved by other traditional algorithms. The results of this research provide a solution with practical potential for aircraft material scheduling problem, which is significantly superior to traditional methods.","PeriodicalId":14766,"journal":{"name":"J. Appl. Math.","volume":"17 1","pages":"1467935:1-1467935:11"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Appl. Math.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2022/1467935","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 maintenance and logistics support of aircraft are critical to the flight safety. The configuration and scheduling of air materials are the basis of maintenance and logistics. This research establishes the model of air material scheduling problem and introduces NSGA-II genetic algorithm with adaptive design to optimize the air material scheduling arrangement. This adaptive design improves the local optimal solution problem of NSGA-II and makes the optimal scheduling of air materials more accurate. In some cases, the improved NSGA-II algorithm is expressed to zero deviation, which is not achieved by other traditional algorithms. The results of this research provide a solution with practical potential for aircraft material scheduling problem, which is significantly superior to traditional methods.