{"title":"航班时刻不确定情况下机场群协调时刻表的稳健优化模型","authors":"Jianzhong Yan, Minghua Hu","doi":"10.3390/aerospace11060457","DOIUrl":null,"url":null,"abstract":"This study develops a robust 0–1 linear optimization programming model for airport group timetable coordination, aiming at assigning each flight at an airport to a unique time slot to avoid conflicts between multiple flights from different airports at the same shared waypoint in an uncertain environment. Flight times between airports and shared waypoints are assumed to have an arbitrary distribution in the interval. Furthermore, some practical constraints, such as the time-varying capacity of each airport, waypoints affected by factors such as weather and traffic control, and maximum delay times for each flight, are considered in this study. The objective is to minimize the total delay time for all flights. The solution is obtained using the RSOME solver. Finally, a real-world case of the Beijing–Tianjin–Hebei airport group, China, is used to optimize the schedules of four airports to prove the accuracy and effectiveness of the method developed in this study. The influence of the budget of uncertainty parameters on model performance is also analyzed.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"28 2","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust Optimization Model of Airport Group Coordinated Timetable with Uncertain Flight Time\",\"authors\":\"Jianzhong Yan, Minghua Hu\",\"doi\":\"10.3390/aerospace11060457\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study develops a robust 0–1 linear optimization programming model for airport group timetable coordination, aiming at assigning each flight at an airport to a unique time slot to avoid conflicts between multiple flights from different airports at the same shared waypoint in an uncertain environment. Flight times between airports and shared waypoints are assumed to have an arbitrary distribution in the interval. Furthermore, some practical constraints, such as the time-varying capacity of each airport, waypoints affected by factors such as weather and traffic control, and maximum delay times for each flight, are considered in this study. The objective is to minimize the total delay time for all flights. The solution is obtained using the RSOME solver. Finally, a real-world case of the Beijing–Tianjin–Hebei airport group, China, is used to optimize the schedules of four airports to prove the accuracy and effectiveness of the method developed in this study. The influence of the budget of uncertainty parameters on model performance is also analyzed.\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":\"28 2\",\"pages\":\"\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.3390/aerospace11060457\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/aerospace11060457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Robust Optimization Model of Airport Group Coordinated Timetable with Uncertain Flight Time
This study develops a robust 0–1 linear optimization programming model for airport group timetable coordination, aiming at assigning each flight at an airport to a unique time slot to avoid conflicts between multiple flights from different airports at the same shared waypoint in an uncertain environment. Flight times between airports and shared waypoints are assumed to have an arbitrary distribution in the interval. Furthermore, some practical constraints, such as the time-varying capacity of each airport, waypoints affected by factors such as weather and traffic control, and maximum delay times for each flight, are considered in this study. The objective is to minimize the total delay time for all flights. The solution is obtained using the RSOME solver. Finally, a real-world case of the Beijing–Tianjin–Hebei airport group, China, is used to optimize the schedules of four airports to prove the accuracy and effectiveness of the method developed in this study. The influence of the budget of uncertainty parameters on model performance is also analyzed.
期刊介绍:
ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications.
The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.