A multivariate adaptive regression splines cutting plane approach for solving a two-stage stochastic programming fleet assignment model

Venkata L. Pilla, Jay M. Rosenberger, Victoria Chen, Narakorn Engsuwan and Sheela Siddappa

European Journal of Operational Research, 2012, vol. 216, issue 1, 162-171

Abstract: The fleet assignment model assigns a fleet of aircraft types to the scheduled flight legs in an airline timetable published six to twelve weeks prior to the departure of the aircraft. The objective is to maximize profit. While costs associated with assigning a particular fleet type to a leg are easy to estimate, the revenues are based upon demand, which is realized close to departure. The uncertainty in demand makes it challenging to assign the right type of aircraft to each flight leg based on forecasts taken six to twelve weeks prior to departure. Therefore, in this paper, a two-stage stochastic programming framework has been developed to model the uncertainty in demand, along with the Boeing concept of demand driven dispatch to reallocate aircraft closer to the departure of the aircraft. Traditionally, two-stage stochastic programming problems are solved using the L-shaped method. Due to the slow convergence of the L-shaped method, a novel multivariate adaptive regression splines cutting plane method has been developed. The results obtained from our approach are compared to that of the L-shaped method, and the value of demand-driven dispatch is estimated.

Keywords: Fleet assignment model; Multivariate adaptive regression splines; L-shaped method; Stochastic programming (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:216:y:2012:i:1:p:162-171

DOI: 10.1016/j.ejor.2011.07.008

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