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Pricing and revenue maximization over a multicommodity transportation network: the nonlinear demand case

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Abstract

This paper is concerned with the design of efficient exact and heuristic algorithms for addressing a bilevel network pricing problem where demand is a nonlinear function of travel cost. The exact method is based on the piecewise linear approximation of the demand function, yielding mixed integer programming formulations, while heuristic procedures are developed within a bilevel trust region framework.

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Authors and Affiliations

  1. Department of Mathematics and Industrial Engineering, École Polytechnique de Montréal, Montreal, Canada

    Aimé Kamgaing Kuiteing & Gilles Savard

  2. Department of Computer Science and Operations Research, Université de Montréal, Montreal, Canada

    Patrice Marcotte

Authors
  1. Aimé Kamgaing Kuiteing
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  2. Patrice Marcotte
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  3. Gilles Savard
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Correspondence to Patrice Marcotte.

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Kuiteing, A.K., Marcotte, P. & Savard, G. Pricing and revenue maximization over a multicommodity transportation network: the nonlinear demand case. Comput Optim Appl 71, 641–671 (2018). https://doi.org/10.1007/s10589-018-0032-0

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  • DOI: https://doi.org/10.1007/s10589-018-0032-0

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