A DISTRIBUTED MULTI-AGENT SYSTEM TO SOLVE AIRLINE OPERATIONS PROBLEMS

Antonio Castro, Eugenio Oliveira

Abstract

An airline schedule very rarely operates as planned. Problems related with aircrafts, crew members and passengers are common and the actions towards the solution of these problems are usually known as operations recovery or disruption management. The Airline Operations Control Center (AOCC) tries to solve these problems with the minimum impact in the airline schedule, with the minimum cost and, at the same time, satisfying all the required safety rules. Usually, each problem is treated separately and some tools have been proposed to help in the decision making process of the airline coordinators. In this paper we present the implementation of a Distributed Multi-Agent System (MAS) that represents the several roles that exist in an AOCC. This MAS deals with several operational bases and for each type of operation problems it has several specialized software agents that implements heuristic solutions and other solutions based in operations research mathematic models and artificial intelligence algorithms. These specialized agents compete to find the best solution for each problem. We present a real case study taken from an AOCC where a crew recovery problem is solved using the MAS. Computational results using a real airline schedule are presented, including a comparison with a solution for the same problem found by the human operators in the Airline Operations Control Center. We show that, even in simple problems and when comparing with solutions found by human operators in the case of this airline company, it is possible to find valid solutions, in less time and with a smaller cost.

References

  1. Abdelgahny, A., Ekollu, G., Narisimhan, R., and Abdelgahny, K., 2004. A Proactive Crew Recovery Decision Support Tool for Commercial Airlines during Irregular Operations, Annals of Operations Research, 127, 309-331.
  2. Barnhart, C., Belobaba, P., and Odoni, A., 2003. Applications of Operations Research in the Air Transport Industry, Transportation Science, 37, 368- 391.
  3. Bellifemine, F., Caire, G., Trucco, T., and Rimassa, G., 2004 JADE Programmer's Guide. JADE 3.3, TILab S.p.A.
  4. Bratu, S., and Barnhart, C., 2006. Flight Operations Recovery: New Approaches Considering Passenger Recovery, Journal of Scheduling, 9,3, 279-298.
  5. Castro, A., and Oliveira, E., 2005. A Multi-Agent System for Intelligent Monitoring of Airline Operations, Proceedings of the Third European Workshop on Multi-Agent Systems, (Brussels, Belgium), 91-102.
  6. Clausen, J., Larsen, A., and Larsen, J.,2005. Disruption Management in the Airline Industry - Concepts, Models and Methods. Technical Report 2005-01, Informatics and Mathematical Modeling, Technical University of Denmark, DTU.
  7. Kohl, N., Larsen, A., Larsen, J., Ross, A., and Tiourline, S., 2004. Airline Disruption Management - Perspectives, Experiences and Outlook. Technical Report CRTR-0407, Carmen Research.
  8. Kohl, N., and Karish, S., 2004. Airline Crew Rostering: Problem Types, Modeling and Optimization, Annals of Operations Research, 127, 223-257.
  9. Lettovsky, L.,1997. Airline Operations Recovery: An Optimization Approach, Ph.D. Thesis, Georgia Institute of Technology, Atlanta, USA.
  10. Malucelli, A., Castro, A., and Oliveira, E., 2006. Crew and Aircraft Recovery Through a Multi-Agent Electronic Market, Proceeding of IADIS e-Commerce 2006, (Barcelona, Spain), 51-58, ISBN: 972-8924-23-2.
  11. Martins, J., and Morgado, E., 1996. Managing Flight Operations, Proceedings of ATTIS'96, (London, England).
  12. Rosenberger, J., Johnson, E., and Nemhauser, G., 2001. Rerouting aircraft for airline recovery, Technical Report TLI-LEC 01-04, Georgia Institute of Technology.
  13. Rosenberger, J., Schaefer, A., Goldsmans, D., Johnson, E., Kleywegt, A., and Nemhauser, G., 2002. A Stochastic Model of Airline Operations, Transportation Science, 36,4, 357-377.
  14. Wooldridge, M., 2002. When is an Agent-Based Solution Appropriate? Introduction to Multiagent Systems, West Sussex, England: John Wiley & Sons, Ltd., pp. 225-226.
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Paper Citation


in Harvard Style

Castro A. and Oliveira E. (2007). A DISTRIBUTED MULTI-AGENT SYSTEM TO SOLVE AIRLINE OPERATIONS PROBLEMS . In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-972-8865-89-4, pages 22-30. DOI: 10.5220/0002404100220030


in Bibtex Style

@conference{iceis07,
author={Antonio Castro and Eugenio Oliveira},
title={A DISTRIBUTED MULTI-AGENT SYSTEM TO SOLVE AIRLINE OPERATIONS PROBLEMS},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2007},
pages={22-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002404100220030},
isbn={978-972-8865-89-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - A DISTRIBUTED MULTI-AGENT SYSTEM TO SOLVE AIRLINE OPERATIONS PROBLEMS
SN - 978-972-8865-89-4
AU - Castro A.
AU - Oliveira E.
PY - 2007
SP - 22
EP - 30
DO - 10.5220/0002404100220030