152 citations · 290 across the 8 of their papers we have counts for
8 papers
Logic-Based Benders Decomposition for Time Slot Management with Mixed Logit Demand
Dorsa Abdolhamidi, Carla Juvin, Virginie Lurkin
This paper develops an exact solution framework for the choice-based time slot management problem under mixed logit demand in attended home delivery systems. The problem jointly op…
A tactical time slot management problem under mixed logit demand
Dorsa Abdolhamidi, Virginie Lurkin
We study the tactical time slot management problem under mixed logit demand for attended home delivery in subscription settings. We propose a static mixed-integer linear programmin…
Operational Research: Methods and Applications
Fotios Petropoulos, Gilbert Laporte, Emel Aktas +79
Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This…
Fighting Pickpocketing using a Choice-based Resource Allocation Model
Loe Schlicher, Virginie Lurkin
Inspired by European actions to fight organised crimes, we develop a choice-based resource allocation model that can help policy makers to reduce the number of pickpocket attempts.…
Stable allocations for choice-based collaborative price setting
Loe Schlicher, Virginie Lurkin
Horizontal agreements can fall within the scope of exemptions to antitrust competition if they are expected to create pro-consumer benefits. Inspired by such horizontal agreements,…
Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms
Gael Lederrey, Virginie Lurkin, Tim Hillel +1
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 da…
An exact algorithm for the static pricing problem under discrete mixed logit demand
Ahmadreza Marandi, Virginie Lurkin
Price differentiation is a common strategy in many markets. In this paper, we study a static multiproduct price optimization problem with demand given by a discrete mixed multinomi…
Enhancing Discrete Choice Models with Representation Learning
Brian Sifringer, Virginie Lurkin, Alexandre Alahi
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 estimatin…