DocumentCode
1939964
Title
A Learning Agent to Assist in Airline Disruption Management
Author
Langerman, J.J. ; Ehlers, E.M.
Author_Institution
Standard Bank of South Africa, Marshalltown
Volume
1
fYear
2005
fDate
28-30 Nov. 2005
Firstpage
321
Lastpage
326
Abstract
Airline disruption management, also known as airline operational scheduling, is becoming an important research topic. During the last few decades great strides have been made to generate optimal schedules. The problem is that when the ideal schedule gets disrupted on the day of operation we need to recover as quickly as possible. A combination of an expert system and a Q-Learning system, implemented as an intelligent agent can be used as a technological approach to solve this problem
Keywords
expert systems; learning systems; scheduling; travel industry; Q-Learning system; airline disruption management; airline operational scheduling; expert system; intelligent agent; learning agent; Africa; Air traffic control; Aircraft; Costs; Expert systems; Humans; Intelligent agent; Job shop scheduling; Optimal scheduling; Processor scheduling;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location
Vienna
Print_ISBN
0-7695-2504-0
Type
conf
DOI
10.1109/CIMCA.2005.1631286
Filename
1631286
Link To Document