A Stochastic Programming Approach to the Airline Crew Scheduling Problem

Authors:
Joyce W. Yen;John R. Birge
Affiliations:
College of Engineering, University of Washington, Seattle, Washington 98195-2180;Graduate School of Business, University of Chicago, Chicago, Illinois 60637
Venue:
Transportation Science
Year:
2006

Citing 10
Cited 13

Integer and combinatorial optimization

Integer and combinatorial optimization
A global approach to crew-pairing optimization

IBM Systems Journal
A multiplier adjustment approach for the set partitioning problem

Operations Research - Supplement
Solving airline crew scheduling problems by branch-and-cut

Management Science
Flight crew scheduling

Management Science
Decision support for airline system operations control and irregular operations

Computers and Operations Research
Solving Large Airline Crew Scheduling Problems: Random Pairing Generation and Strong Branching

Computational Optimization and Applications
Branch-And-Price: Column Generation for Solving Huge Integer Programs

Operations Research
The Operational Airline Crew Scheduling Problem

Transportation Science
Airline Crew Recovery

Transportation Science

Planning for Robust Airline Operations: Optimizing Aircraft Routings and Flight Departure Times to Minimize Passenger Disruptions

Transportation Science
Robust crew pairing for managing extra flights

Computers and Operations Research
Integrated Airline Fleet and Crew Robust Planning

Transportation Science
Disruption management in the airline industry-Concepts, models and methods

Computers and Operations Research
A multi-objective approach for robust airline scheduling

Computers and Operations Research
An iterative approach to robust and integrated aircraft routing and crew scheduling

Computers and Operations Research
A comparison of stochastic programming and bi-objective optimisation approaches to robust airline crew scheduling

OR Spectrum
On the two-stage problem of linear stochastic programming with quantile criterion and discrete distribution of the random parameters

Automation and Remote Control
Robust Airline Schedule Planning: Minimizing Propagated Delay in an Integrated Routing and Crewing Framework

Transportation Science
Railway Rolling Stock Planning: Robustness Against Large Disruptions

Transportation Science
Solving a robust airline crew pairing problem with column generation

Computers and Operations Research
Vessel routing and scheduling under uncertainty in the liquefied natural gas business

Computers and Industrial Engineering
A model of resilient supply chain network design: A two-stage programming with fuzzy shortest path

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Traditional methods model the billion-dollar airline crew scheduling problem as deterministic and do not explicitly include information on potential disruptions. Instead of modeling the crew scheduling problem as deterministic, we consider a stochastic crew scheduling model and devise a solution methodology for integrating disruptions in the evaluation of crew schedules. The goal is to use that information to find robust solutions that better withstand disruptions. Such an approach is important because we can proactively consider the effects of certain scheduling decisions. By identifying more robust schedules, cascading delay effects are minimized. In this paper we describe our stochastic integer programming model for the airline crew scheduling problem and develop a branching algorithm to identify expensive flight connections and find alternative solutions. The branching algorithm uses the structure of the problem to branch simultaneously on multiple variables without invalidating the optimality of the algorithm. We present computational results demonstrating the effectiveness of our branching algorithm.