返回
A multi-objective genetic algorithm for robust flight scheduling using simulation
DOI:10.1016/j.ejor.2005.12.014.png)
摘要
En 中文
Traditional methods of developing flight schedules generally do not take into consideration disruptions that may arise during actual operations. Potential irregularities in airline operations such as equipment failure are not adequately considered during the planning stage of a flight schedule. As such, flight schedules cannot be met as planned and their performance is compromised, which may eventually lead to huge losses in revenue for airlines. In this paper, we seek to improve the robustness of a flight schedule by re-timing its departure times. The problem is modeled as a multi-objective optimization problem, and a multi-objective genetic algorithm (MOGA) is developed to solve the problem. To evaluate flight schedules, SIMAIR 2.0, a simulation model which simulates airline operations under operational irregularities, has been employed. The simulation results indicate that we are able to develop schedules with better operation costs and on-time performance through the application of MOGA. (c) 2005 Elsevier B.V. All rights reserved.
Keyword:
genetic algorithms
scheduling
simulation
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6
论文数:
2.2W
被引数:
6.4W
机构
暂无机构信息
引用论文
Chronic High Glyphosate Exposure Delays Individual Worker Bee (Apis mellifera L.) Development under Field Conditions
Insects
IF0
没有更多内容

