Nonstationary Markov Chain Framework for Optimizing Dedicated Check-in Service

The arrivals of passengers at airport check-in counters represent a random process with variable arrival rates over time. Since the arrivals generally tend to occur at higher rates close to the beginning and end of the scheduled check-in, it is worth determining when additional counter(s) should be opened or closed. This problem becomes more complicated for large airlines at busy airports where they manage the check-in process for multiple flights. A model is developed here for optimizing the number of check-in counters as well as their opening and closing times. The check-in process is modeled as a nonstationary Markov chain and a parallel genetic algorithm with an integrated fourth order Runge-Kutta method is developed to optimize the check-in service. The authors minimize the airline’s cost while providing the desired level of service.

• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Markovic, Nikola
  • Drobnjak, Zeljko
  • Schonfeld, Paul
• Conference:
  • Transportation Research Board 91st Annual Meeting
  • Location: Washington DC, United States
  • Date: 2012-1-22 to 2012-1-26
• Date: 2012

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 17p
• Monograph Title: TRB 91st Annual Meeting Compendium of Papers DVD

Subject/Index Terms

• TRT Terms: Airport operations; Airport ticket counters; Genetic algorithms; Markov chains; Optimization
• Subject Areas: Aviation; Operations and Traffic Management; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01365399
• Record Type: Publication
• Report/Paper Numbers: 12-3902
• Files: TRIS, TRB
• Created Date: Mar 20 2012 12:16PM