{"title":"GraGA:一种基于图的航空机组调度遗传算法","authors":"H. Ozdemir, C. Mohan","doi":"10.1109/TAI.1999.809761","DOIUrl":null,"url":null,"abstract":"Crew scheduling is an NP-hard constrained combinatorial optimization problem, which is very important for the airline industry. We propose a genetic algorithm, GraGA, to solve this problem. A new graph based representation utilizes memory effectively, and provides a framework in which we can easily develop various genetic operators.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"GraGA: a graph based genetic algorithm for airline crew scheduling\",\"authors\":\"H. Ozdemir, C. Mohan\",\"doi\":\"10.1109/TAI.1999.809761\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Crew scheduling is an NP-hard constrained combinatorial optimization problem, which is very important for the airline industry. We propose a genetic algorithm, GraGA, to solve this problem. A new graph based representation utilizes memory effectively, and provides a framework in which we can easily develop various genetic operators.\",\"PeriodicalId\":194023,\"journal\":{\"name\":\"Proceedings 11th International Conference on Tools with Artificial Intelligence\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 11th International Conference on Tools with Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1999.809761\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 11th International Conference on Tools with Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1999.809761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GraGA: a graph based genetic algorithm for airline crew scheduling
Crew scheduling is an NP-hard constrained combinatorial optimization problem, which is very important for the airline industry. We propose a genetic algorithm, GraGA, to solve this problem. A new graph based representation utilizes memory effectively, and provides a framework in which we can easily develop various genetic operators.