Fleet assignment model based on multi-objective linear programming: a case study for a new-established airline

Mengyuan Lu; Xiao Zhang; Jinmei Ge

doi:10.1117/12.2668555

16 February 2023 Fleet assignment model based on multi-objective linear programming: a case study for a new-established airline

Mengyuan Lu, Xiao Zhang, Jinmei Ge

Author Affiliations +

Proceedings Volume 12591, Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022); 125911E (2023) https://doi.org/10.1117/12.2668555
Event: 6th International Conference on Traffic Engineering and Transportation System (ICTETS 2022), 2022, Guangzhou, China

Abstract

Fleet assignment problem is a combinatorial optimization problem with multiple objectives and constraints. This paper established a mathematical model of the fleet assignment problem for diverse optimization objectives of the problem. The objectives are to find the minimum number of aircraft needed to operate the network and assign the optimal fleet to each flight leg in order to maximize the total profit. LINDO software was utilized to run the programming and obtain the optimal solution. This paper also demonstrated a calculation example by assuming a new-established airline in the U.S. with its hub and spoke network being analyzed. The algorithm is proved to be feasible and effective when examining in Sabre software, which is not available in domestic Chinese market. The methodology is not only conducive to the safe and punctual operation of flights, but also guides airlines to optimize the utilization of the fleet and effectively reduce the operation and maintenance costs. It is practical to airline schedulers and will promote the development of system and software in Chinese market.

Citation Download Citation

Mengyuan Lu, Xiao Zhang, and Jinmei Ge "Fleet assignment model based on multi-objective linear programming: a case study for a new-established airline", Proc. SPIE 12591, Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022), 125911E (16 February 2023); https://doi.org/10.1117/12.2668555

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