The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/12852824

Marandi, Ahmadreza; Lurkin, Virginie (2020): LiBiT algorithm to solve static pricing problems under mixed multinomial logit demand. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/12852824.v1

Dataset

• Applied Mathematics
• Econometrics
• Numerical and Computational Mathematics

Branching Methods, convex optimization, Convex Relaxation, mixed logit model, nonlinear optimization model, static multi-product pricing

2020

CC BY-NC 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Ahmadreza Marandi , Virginie Lurkin

Price differentiation is a common strategy for many operators. We study a static multiproduct price optimization problem with demand given by a continuous mixed multinomial logit model. To solve this new problem, we design an efficient iterative optimization algorithm that asymptotically converges to the optimal solution. To this end, a linear optimization (LO) problem is formulated, based on the trust-region approach, to find a "good" feasible solution and approximate the problem from below. Another LO problem is designed using piecewise linear relaxations to approximate the optimization problem from above. Then, we develop a new branching method to tighten the optimality gap.

• 2020-08-24 first online, published, posted

4TU.ResearchData

• https://arxiv.org/abs/2005.07482

https://github.com/ahmadreza-marandi/Static_Pricing_problem

Eindhoven University of Technology, Department of Industrial Engineering & Innovation Sciences, Operations, Planning, Accounting, and Control