{"title":"SEA航线网络优化及交叉航路点位置研究","authors":"Z. Zhong, Jian-Hui Richard Yee","doi":"10.1109/MESA.2018.8449170","DOIUrl":null,"url":null,"abstract":"This study was conducted in three stages through a number of single and multi-objective Particle Swarm Optimization (PSO) simulations. In the first two stages, simulations were performed to assess the feasibility and effectiveness of the optimization algorithms and to study the efficiency of the Air Route Networks (ARNs) based on these algorithms. In the third stage, these PSO algorithms were applied to a South East Asia focused ARN. The ARN's efficiency indicators used were two principle objectives. Findings from this study can be used as a basis for future ARN designs. The optimization algorithms studied can serve as fundamental templates for future ARN simulation analyses.","PeriodicalId":138936,"journal":{"name":"2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Study of Optimization of Air Route Networks and Locations of Crossing Waypoints for SEA\",\"authors\":\"Z. Zhong, Jian-Hui Richard Yee\",\"doi\":\"10.1109/MESA.2018.8449170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study was conducted in three stages through a number of single and multi-objective Particle Swarm Optimization (PSO) simulations. In the first two stages, simulations were performed to assess the feasibility and effectiveness of the optimization algorithms and to study the efficiency of the Air Route Networks (ARNs) based on these algorithms. In the third stage, these PSO algorithms were applied to a South East Asia focused ARN. The ARN's efficiency indicators used were two principle objectives. Findings from this study can be used as a basis for future ARN designs. The optimization algorithms studied can serve as fundamental templates for future ARN simulation analyses.\",\"PeriodicalId\":138936,\"journal\":{\"name\":\"2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MESA.2018.8449170\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MESA.2018.8449170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study of Optimization of Air Route Networks and Locations of Crossing Waypoints for SEA
This study was conducted in three stages through a number of single and multi-objective Particle Swarm Optimization (PSO) simulations. In the first two stages, simulations were performed to assess the feasibility and effectiveness of the optimization algorithms and to study the efficiency of the Air Route Networks (ARNs) based on these algorithms. In the third stage, these PSO algorithms were applied to a South East Asia focused ARN. The ARN's efficiency indicators used were two principle objectives. Findings from this study can be used as a basis for future ARN designs. The optimization algorithms studied can serve as fundamental templates for future ARN simulation analyses.