Publications de Virginie Janine Camille Lurkin

Price-based regulation of oligopolistic markets under discrete choice models of demand

Michel Bierlaire, Virginie Janine Camille Lurkin, Stefano Bortolomiol

We propose a framework to find optimal price-based policies to regulate markets characterized by oligopolistic competition and in which consumers make a discrete choice among a finite set of alternatives. With this framework, we can include general discret ...

EPFL2021

Price-based regulation of oligopolistic markets under discrete choice models of demand

Michel Bierlaire, Virginie Janine Camille Lurkin, Stefano Bortolomiol

We propose a framework to find optimal price-based policies to regulate markets characterized by oligopolistic competition and in which consumers make a discrete choice among a finite set of alternatives. The framework accommodates general discrete choice ...

2021

A Simulation-Based Heuristic to Find Approximate Equilibria with Disaggregate Demand Models

Michel Bierlaire, Virginie Janine Camille Lurkin, Stefano Bortolomiol

Oligopolistic competition occurs in various transportation markets. In this paper, we introduce a framework to find approximate equilibrium solutions of oligopolistic markets in which demand is modeled at the disaggregate level using discrete choice models ...

INFORMS2021

Enhancing discrete choice models with representation learning

Alexandre Massoud Alahi, Virginie Janine Camille Lurkin

In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of the utility specif ...

2020

Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

Michel Bierlaire, Timothy Michael Hillel, Virginie Janine Camille Lurkin, Gael Lederrey

The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the esti ...

2020

Airline customers connection time preferences in domestic U.S. markets

Michel Bierlaire, Virginie Janine Camille Lurkin

Within the United States, there have been evolving perceptions on the benefits and disadvantages of using peaked flight schedules. Arguments in favor of using peaked schedules have centered on a traditional assumption that consumers prefer itineraries with ...

2019

Stochastic Optimization with Adaptive Batch Size: Discrete Choice Models as a Case Study

Michel Bierlaire, Timothy Michael Hillel, Virginie Janine Camille Lurkin, Gael Lederrey

The 2.5 quintillion bytes of data created each day brings new opportunities, but also new stimulating challenges for the discrete choice community. Opportunities because more and more new and larger data sets will undoubtedly become available in the future ...

2019

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