Crew Pairing and Aircraft Routing for On-Demand Aviation with Time Window

4 Pages Posted: 22 Oct 2005

See all articles by Yufeng Yao

Yufeng Yao

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE)

Wei Zhao

Georgia Institute of Technology - School of Aerospace Engineering

Ozlem Ergun

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE)

Ellis Johnson

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE)

Abstract

On-demand air transportation provides passengers a convenient option flying point-to-point directly anytime at their requests. Although it's convenient to customers, this type of non-scheduled service posts great challenge to the management companies, who must serve customer demand by efficiently arranging their aircraft.

A set-partitioning model is proposed to optimize the crew pairing and aircraft routing problem with minimum cost. The model takes into account multiple types of aircraft and FAA crew regulations. It is implemented with object-oriented programming and solved using CPLEX. In the model, a time window strategy is considered to allow flexible departure time during high demand day. The results show great improvement on cost savings over the company's original schedule. Especially, the flexible departure time emerges significant improvement on aircraft utilization and charter reduction. Moreover, the proposed methodology offers an efficient approach to evaluate business strategies, and provides valuable insight to help business decision-making.

Keywords: Crew scheduling, column generation, rolling horizon, K shortest paths

JEL Classification: C61, L93, R40

Suggested Citation

Yao, Yufeng and Zhao, Wei and Ergun, Ozlem and Johnson, Ellis, Crew Pairing and Aircraft Routing for On-Demand Aviation with Time Window. Available at SSRN: https://ssrn.com/abstract=822265 or http://dx.doi.org/10.2139/ssrn.822265

Yufeng Yao (Contact Author)

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE) ( email )

765 Ferst Drive
Atlanta, GA 30332-0205
United States

Wei Zhao

Georgia Institute of Technology - School of Aerospace Engineering ( email )

270 Ferst Drive
Atlanta, GA 30332-0150
United States

Ozlem Ergun

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE) ( email )

765 Ferst Drive
Atlanta, GA 30332-0205
United States

Ellis Johnson

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE) ( email )

765 Ferst Drive
Atlanta, GA 30332-0205
United States

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