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System Operations Advisor: A Real-Time Decision Support System for Managing Airline Operations at United Airlines

Author

Listed:
  • Ananda Rakshit

    (United Airlines, Corporate Research and Development, Chicago, Illinois 60666)

  • Nirup Krishnamurthy

    (United Airlines, Corporate Research and Development, Chicago, Illinois 60666)

  • Gang Yu

    (Department of Management Science and Information Systems, Graduate School of Business, University of Texas at Austin, Austin, Texas 78712)

Abstract

Managing daily operations for United Airlines with its size and geographic scope of operations is complex and challenging. Because resources are tightly coupled, even minor perturbations could erode planned operations. United Airlines deploys the System Operations Advisor (SOA), a real-time decision support system at its operations control center (OCC) to increase the effectiveness of its operational decisions. We developed the SOA and implemented it in August 1992. It has been in operation since then. From October 1993 to March 1994, its application saved more than 27,000 minutes of potential delays, which translates to $540,000 savings in delay costs, and the number of flight delays charged to aircraft controllers in systems operations control has dropped by 50 percent since 1992.

Suggested Citation

  • Ananda Rakshit & Nirup Krishnamurthy & Gang Yu, 1996. "System Operations Advisor: A Real-Time Decision Support System for Managing Airline Operations at United Airlines," Interfaces, INFORMS, vol. 26(2), pages 50-58, April.
    • Handle: RePEc:inm:orinte:v:26:y:1996:i:2:p:50-58
    DOI: 10.1287/inte.26.2.50
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    Citations

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    Cited by:

    1. S Eom & E Kim, 2006. "A survey of decision support system applications (1995–2001)," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(11), pages 1264-1278, November.
    2. Brouer, Berit D. & Dirksen, Jakob & Pisinger, David & Plum, Christian E.M. & Vaaben, Bo, 2013. "The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping," European Journal of Operational Research, Elsevier, vol. 224(2), pages 362-374.
    3. Zhang, Yu, 2008. "Real-time Inter-modal Strategies for Airline Schedule Perturbation Recovery and Airport Congestion Mitigation under Collaborative Decision Making (CDM)," University of California Transportation Center, Working Papers qt2k44c9tx, University of California Transportation Center.
    4. Dennis F.X. Mathaisel, 1997. "Decision Support for Airline Schedule Planning," Journal of Combinatorial Optimization, Springer, vol. 1(3), pages 251-275, October.
    5. Stojkovic, Goran & Soumis, François & Desrosiers, Jacques & Solomon, Marius M., 2002. "An optimization model for a real-time flight scheduling problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(9), pages 779-788, November.
    6. Gang Yu & Michael Argüello & Gao Song & Sandra M. McCowan & Anna White, 2003. "A New Era for Crew Recovery at Continental Airlines," Interfaces, INFORMS, vol. 33(1), pages 5-22, February.
    7. Moudani, Walid El & Mora-Camino, Félix, 2000. "A dynamic approach for aircraft assignment and maintenance scheduling by airlines," Journal of Air Transport Management, Elsevier, vol. 6(4), pages 233-237.
    8. Dhar, Deepak, 1999. "The Abelian sandpile and related models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 263(1), pages 4-25.
    9. Thengvall, Benjamin G. & Yu, Gang & Bard, Jonathan F., 2001. "Multiple fleet aircraft schedule recovery following hub closures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(4), pages 289-308, May.
    10. Bard, Jonathan F. & Mohan, Dinesh Natarajan, 2008. "Reallocating arrival slots during a ground delay program," Transportation Research Part B: Methodological, Elsevier, vol. 42(2), pages 113-134, February.
    11. Paul M. Carlson, 2000. "Exploiting the Opportunities of Collaborative Decision Making: A Model and Efficient Solution Algorithm for Airline Use," Transportation Science, INFORMS, vol. 34(4), pages 381-393, November.
    12. T. Andersson * & P. Värbrand, 2004. "The flight perturbation problem," Transportation Planning and Technology, Taylor & Francis Journals, vol. 27(2), pages 91-117, March.
    13. Joyce W. Yen & John R. Birge, 2006. "A Stochastic Programming Approach to the Airline Crew Scheduling Problem," Transportation Science, INFORMS, vol. 40(1), pages 3-14, February.
    14. Obrad Babić & Milica Kalić & Goran Pavković & Slavica Dožić & Mirjana Čangalović, 2010. "Heuristic approach to the airline schedule disturbances problem," Transportation Planning and Technology, Taylor & Francis Journals, vol. 33(3), pages 257-280, February.
    15. Hu, Yuzhen & Song, Yan & Zhao, Kang & Xu, Baoguang, 2016. "Integrated recovery of aircraft and passengers after airline operation disruption based on a GRASP algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 97-112.
    16. Jay M. Rosenberger & Ellis L. Johnson & George L. Nemhauser, 2003. "Rerouting Aircraft for Airline Recovery," Transportation Science, INFORMS, vol. 37(4), pages 408-421, November.

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