Publications by Michel Bierlaire

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Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of a household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly based on the individual decision-making process, which are limited in their demonstration of behaviour. We simulate multiple intra-household interaction dimensions within the same framework and capture the coordination of the activity scheduling decisions amon

Seaport container terminals are source of many interesting large-scale optimization problems, which arise in the management of operations at several decision levels. In this paper we firstly illustrate a recently proposed framework, called two-stage column generation (Salani and Vacca, 2008), which is suitable for a particular class of large-scale problems, where the structure of the original formulation, namely the presence of a combinatorial number of decision variables, does not allow for straightforward

We propose and validate a model for pedestrian walking behavior, based on discrete choice modeling. Two main types of behavior are identified: unconstrained and constrained. By unconstrained, we refer to behavior patterns which are independent from other i ...

The vehicle sharing systems (VSSs) are becoming more popular due to both financial and environmental effects. On the other hand, they face many challenges, such as inventory management of the vehicles and parking spots, vehicle imbalance, pricing strategie ...

Increasing environmental concerns drive interest in sustainable solutions across various fields. Vehicle sharing systems such as one-way station-based bike sharing systems (BSSs) offer one such solution in transportation, although they pose operational cha ...

In this paper, we discuss some of the issues that arise with the computation of the implied value of travel-time savings in the case of discrete choice models allowing for random taste heterogeneity. We specifically look at the case of models producing a n ...

We propose a multiplicative specification of a discrete choice model that renders choice probabilities independent of the scale of the utility. The scale can thus be random with unspecified distribution. The model mostly outperforms the classical additive formulation over a range of stated choice data sets. In some cases, the improvement in likelihood is greater than that obtained from adding observed and unobserved heterogeneity to the additive specification. The multiplicative specification makes it unnec

Generalised Extreme Value models provide an interesting theoret- ical framework to develop closed-form random utility models. Unfor- tunately, few instances of this family are to be found as operational models in practice. The form of the model, based on a generating function G which must satisfy specific properties, is rather compli- cated. Fundamentally, it is not an easy task to translate an intuitive perception of the correlation structure by the modeller into a concrete G function. And even if the mode

We propose a multiplicative specification of a discrete choice model that renders choice probabilities independent of the scale of the utility. The scale can thus be random with unspecified distribution. The model mostly outperforms the classical additive formulation over a range of stated choice data sets. In some cases, the improvement in likelihood is greater than that obtained from adding bserved and unobserved heterogeneity to the additive specification. The multiplicative specification makes it unnece

We develop and test a new approach for measuring travel well-being that accounts for the routine nature of travel. We postulate that when people are in a routine, they dont fully consider their travel happiness. Only when people evaluate their options and reconsider their decisions will they think of their travel happiness. Consequently, a travel happiness measure collected at the time of decision-making might be a more relevant measure of their happiness that correlates better with behavior. To test this h

This paper proposes a block logit (BL) model, which is an alternative approach to incorporating covariance between the random utilities of alternatives into a GEV random utility maximization model. The BL is similar to the nested logit (NL), in that it is a restricted form of a network GEV (NGEV) model. The NL is a NGEV model where all of the allocation parameters have been fixed with a value equal to zero or one. The BL model proposed in this paper imposes the other possible constraint on the parameters of

Most existing state-of-the-art synthetic generation methods produce static snapshots of data that fail to adapt to demographic changes over time, which makes them quickly outdated. This paper introduces an adaptive approach to synthetic population generation using a one-step Gibbs Sampler that allows for the maintenance of synthetic data by integrating new information adaptively, rather than requiring a complete regeneration of datasets each time an update is necessary. We compare existing independent regen

Demand analysis is more and more critical in the transportation context. Discrete choice models methodology provide an appropriate framework to capture the behaviour of the actors of transportation systems and, consequently, to forecast the demand. Recently, the cross-nested logit (CNL) model has received significant attention in the literature to capture decisions such as mode choice (Vovsha, 1997), departure time choice (Small, 1987) and route choice (Vovsha and Bekhor, 1998). Its general structure is app

Optimization algorithms are rarely mentioned in the discrete choice literature. One reason may be that classic Newton-Raphson methods have been rather successful in estimating discrete choice parameters on available data sets of limited size. However, thanks to recent advances in data collection, abundant data about choice situations become more and more available, and state-of-the-art algorithms can be computationally burdensome on these massive datasets. In this paper, inspired by the good practices from

The near arrival of electric vehicles on the car market generates a need for new models in order to understand and predict the impact it has on the current market shares. This research aims at providing contributions regarding several issues related to the evaluation of the demand for electric vehicles, i.e. related to the survey design, demand models and forecasting. In this paper we focus on the first of these three methodological issues. We present the design of a stated preference survey which will enab

UrbanSim is an integrated transportation land-use model that has been under development since the late 1990s. It has received a significant amount of attention in the integrated modeling community. It is well known for its disaggregated approach. A number ...

Energy and transport demand can both be considered as being derived from an individual’s activity participation. As such, both energy and transport demand are inherently linked: completing activities inside the home generates residential energy demand, where completing activities outside the home generates transportation and non-residential energy demand. Whilst there are several works in the literature that focus on either energy or transportation demand, there remain very few studies which explicitly inve

We integrate a probabilistic demand model in the train timetabling problem. We use a logit model that we calibrate to reflect the known demand elasticities. We further include a competing operator as an opt-out option for the passengers. Subsequently, we integrate the train timetabling problem with a ticket pricing problem. We solve the elastic passenger centric train timetabling problem for various types of timetables using a simulated annealing heuristic on a case study of Israeli Railways. The results of

The generation of synthetic households is challenging due to the necessity of maintaining consistency between the two layers of interest: the household itself, and the individuals composing it. Hence, the problem is typically tackled in two steps, first fo ...

Michel Bierlaire

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Simulating intra-household interactions for in- and out-of-home activity scheduling

Two-stage column generation and applications in container terminal management

Specification, estimation and validation of a pedestrian walking behavior model

An optimization framework for light electric vehicle sharing systems

Bike sharing systems: The impact of precise trip demand forecasting on operational efficiency in different city structures

Estimation of value of travel-time savings using Mixed Logit models

Discrete choice models with multiplicative error terms

A general and operational representation of GEV models

Circumventing the problem of the scale: discrete choice models with multiplicative error terms

Happiness and travel behavior modification

Properties, advantages, and drawbacks of the block logit model

Adaptive synthetic generation using one-step Gibbs Sampler

Normalization and correlation of cross-nested logit models

SNM: Stochastic Newton Method for Optimization of Discrete Choice Models

Modeling demand for electric vehicles: the effect of car users' attitudes and perceptions

Adaptive synthetic generation using one-step Gibbs Sampler

Development of prototype UrbanSim models

Integrated models of transport and energy demand: A literature review and framework

Train Timetable Design Under Elastic Passenger Demand

One-step Gibbs sampling for the generation of synthetic households