Publications associées à Quasilinear utility

OASIS: An integrated optimisation framework for activity scheduling

Activity-based models offer the potential for a far deeper understanding of daily mobility behaviour than trip-based models. Based on the fundamental assumption that travel demand is derived from the need to do activities, they are flexible tools that aim ...

EPFL2024

Capturing trade-offs between daily scheduling choices

Michel Bierlaire, Timothy Michael Hillel, Janody Pougala

We propose a new modelling approach for daily activity scheduling which integrates the different daily scheduling choice dimensions (activity participation, location, schedule, duration and transportation mode) into a single optimisation problem. The funda ...

ELSEVIER SCI LTD2022

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 ...

2022

Integrating advanced discrete choice models in mixed integer linear optimization

Michel Bierlaire, Meritxell Pacheco Paneque, Bernard Gendron

In many transportation systems, a mismatch between the associated design and planning decisions and the demand is typically encountered. A tailored system is not only appealing to operators, which could have a better knowledge of their operational costs, b ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Scheduling trips through a bottleneck: monotonicity and stability

Nikolaos Geroliminis, Raphael Ali Francis Lamotte

This paper investigates the stability of departure time choice within a population of commuters that need to pass through a bottleneck of constant capacity. It is shown that the corresponding utility function is monotonic if and only if the marginal utilit ...

2019

Weak teachers: assisted specification of discrete choice models using ensemble learning algorithms

Timothy Michael Hillel

Discrete Choice Models (DCMs) have a distinct advantage over Machine Learning (ML) classification algorithms, in that they employ a highly interpretable linear structure. However, a key drawback of DCMs compared to ML is the need to specify the utility fun ...

2019

Synthesis of single and interplant non-isothermal water networks

François Maréchal, Maziar Kermani

This paper addresses the synthesis problem of non-isothermal water networks using a mathematical programming approach. A heat-integrated water network superstructure and its corresponding mixed integer nonlinear programming (MINLP) model is proposed for th ...

2017

Measurement system design for civil infrastructure using expected utility

Ian Smith, James-Alexandre Goulet, Romain Pasquier

For system identification, most sensor-placement strategies are based on the minimization of the model-parameter uncertainty. However, reducing the uncertainty in remaining-life prognosis of structures is often more relevant. This paper proposes an optimiz ...

Elsevier2017

A Robust Resolution of Newcomb's Paradox

Thomas Alois Weber

Newcomb's problem is viewed as a dynamic game with an agent and a superior being as players. Depending on whether or not a risk-neutral agent's confidence in the superior being, as measured by a subjective probability assigned to the move order, exceeds a ...

2016

Bidder optimal assignments for general utilities

Monika Henzinger, Ingmar Weber

We study the problem of matching bidders to items where each bidder i has general, strictly monotonic utility functions u(i,j)(p(j)) expressing his utility of being matched to item j at price p(j). For this setting we prove that a bidder optimal outcome al ...

Elsevier Science Bv2013