Kihwan Bae

Asst Professor

Ki-Hwan Bae graduated from Industrial and Systems Engineering at Virginia Tech, earning Ph.D. in Operations Research in 2010. His doctoral research is about airline scheduling models integrating schedule design, fleet assignment, aircraft routing, and crew scheduling. In addition, he also worked on the Small Aircraft Transportation System project sponsored by NASA. Prior to that, he studied at Purdue University focusing on simulation and received his master's degree in Industrial Engineering. Before joining the Department of Industrial Engineering at University of Louisville in 2013, he had experience of working as a business strategy analyst in the telecommunication industry.

Education

  • Ph.D. in Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, 2010
  • M.S. in Industrial Engineering, Purdue University, 2004
  • B.S. in Industrial and System Engineering, Yonsei University, 2002

Publications

An Integrated Approach for Airline Flight Selection and Timing, Fleet Assignment, and Aircraft Routing- 2013

Airline profits critically depend on the nature and efficiency of service they provide, and accrue from a complex planning process involving schedule design, fleet assignment, aircraft routing, and crew scheduling, which are interrelated to each other within the overall system. We propose in this paper a model that integrates certain aspects of the schedule design, fleet assignment, and aircraft-routing processes, while considering flight retiming and demand recapture issues, along with optional legs, itinerary-based demands, and multiple fare classes. Maintenance routing decisions, as well as through-flight opportunities, are additionally incorporated in our model, and we apply the reformulation-linearization technique to reduce its complexity while introducing hierarchical symmetry-breaking constraints, along with other classes of valid inequalities, to enhance its solvability. A Benders’ decomposition-based method is designed to handle the resulting large-scale model formulation. Computational results using real data obtained from United Airlines are presented to demonstrate the potential profitability in applying the proposed approach.

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