Publication

Integrated airline schedule planning with supply-demand interactions

Michel Bierlaire
2011
Talks

Abstract

In this study, we integrate a schedule design and fleet assignment model and a demand model into an optimization problem to maximize the revenue of an airline. The model considers spill and recapture effects to cope with capacity restrictions. For the demand modeling, fares, fare classes, departure times and number of stops are modeled by linear and nonlinear specifications. A heuristic method is proposed to deal with the high complexity of the resulting mixed integer nonlinear problem.

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Michel Bierlaire
2011
Talks

Abstract

Official source

Related concepts (26)

Optimization problem

In mathematics, computer science and economics, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization problems can be divided into two categories, depending on whether the variables are continuous or discrete: An optimization problem with discrete variables is known as a discrete optimization, in which an object such as an integer, permutation or graph must be found from a countable set.

Combinatorial optimization

Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, where the set of feasible solutions is discrete or can be reduced to a discrete set. Typical combinatorial optimization problems are the travelling salesman problem ("TSP"), the minimum spanning tree problem ("MST"), and the knapsack problem. In many such problems, such as the ones previously mentioned, exhaustive search is not tractable, and so specialized algorithms that quickly rule out large parts of the search space or approximation algorithms must be resorted to instead.

Mathematical optimization

Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.

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Integrated airline schedule planning with supply-demand interactions

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