Publications by Michel Bierlaire

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This paper analyses and compares different policy scenarios as well as discusses price elasticities and willingness to pay and to accept using revealed preference data from the French new-car market in 2014 by means of a cross-nested logit (CNL) model. We focus particularly on electric and hybrid vehicles. We use interactions between the cost (both fixed and running costs) and the household income in order to analyze the sensitivity towards different policy scenarios per income level. Results show that the

UrbanSim is an integrated transportation land-use model that has been under development since the late 1990s. It has received a fair bit of attention in the integrated modeling community. Its notoriety comes primarily from its disaggregated approach. A number of papers describing the application of UrbanSim have appeared in the formal and grey literatures. Some of these papers report on successful applications of UrbanSim with little description of the amount of effort required to develop an operational mod

In this paper we investigate the use of a smartphone database to explore influences on travel behavior. Our aim is to exploit the rich individual-level data available from the smartphone to study the influence of communication and social contacts (collected via phone call and sms logs) on spatial movement (collected via GPS). An advantage of smartphone data is the ability to collect such rich data without user input over a long period of time, and the disadvantage is the difficulty associated with processin

Pollution, congestion and urbanistic considerations are leading to a change in the use of private vehicles in dense city centers. More frequently, the last-mile is covered with systems such as public transport, car sharing and bike sharing as well as an in ...

The conditional indirect utility of many random utility maximization (RUM) discrete choice models is specified as a sum of an index V depending on observables and an independent random term P. In general, the universe of RUM consistent models is much large ...

Activity-based models offer the potential of a far deeper understanding of daily mobility behaviour than trip-based models. However, activity-based models used both in research and practice have often relied on applying sequential choice models between sub ...

The choice-based pricing problem (CPP) consists in optimizing product prices while accounting for consumer preferences and potential capacity constraints. Demand is typically modeled using a discrete choice model (DCM). We introduce the Breakpoint Heuristic Algorithm (BHA) to address the CPP with and without capacity constraints as well as an extension of the Breakpoint Exact Algorithm (BEA) to handle capacities, together with valid inequalities for the QCQP-L (quadratically constrained quadratic program wi

When using random utility models for a route choice problem, choice set generation and correlation among alternatives are two issues that make the modeling complex. In this paper we discuss different models capturing path overlap. First, we analyze several formulations of the Path Size Logit model proposed in the literature and show that the original formulation should be used. Second, we propose a modeling approach where the path overlap is captured with a subnetwork. A subnetwork is a simplification of th

In Switzerland, the largest railway stations are called RailCities by the Swiss Railways. It emphasizes their transformation into places to perform different activities, similar to a small-scale city. Concerns are similar than in urban areas: costs of new infrastructure, traffic congestion, land scarcity. The activity-based approach models the activity participation patterns. Traveling is seen as a derived demand from the need to pursue activities. In the pedestrian context, postulate rules, such as the hom

Discrete choice models in general and random utility models in particular may be intractable when the number of alternatives is large. In the transportation context, it typically happens for route choice and destination choice models. In the specific case of the widely used multinomial logit model, it has been shown that the model could be estimated as if the choice was made among a subset of the alternatives. In this paper, we propose to design the sampling of alternatives based on a Principal Component An

The application of kernel-based Machine Learning (ML) techniques to discrete choice modelling using large datasets often faces challenges due to memory requirements and the considerable number of parameters involved in these models. This complexity hampers ...

The generation of synthetic populations through simulation methods is an important research topic and has a key application in agent-based modeling of transport and land use. The next step in this research area is the generation of complete synthetic house ...

We propose a new heuristic for nonlinear global optimization combining a variable neighbourhood search framework with a modified trust-region algorithm as local search. The proposed method presents the capability to prematurely interrupt the local search i ...

We solve a rich logistical problem inspired from practice, in which a heterogeneous fixed fleet of vehicles is used for collecting recyclable waste from large containers over a finite planning horizon. Each container is equipped with a sensor, which communicates its level at the start of the day. Given a history of observations, a forecasting model is used to estimate the point demand forecasts as well as a forecasting error representing the level of uncertainty. The problem falls under the framework of the

The planning of national power systems is traditionally based on long-term forecasts of electricity demand and fuel prices. However, over such long time horizons (20-50 years), these forecasts often prove to be inaccurate. As an example, wrong projections ...

Allowing for variations in behaviour across respondents is one of the most fundamental principles in discrete choice modelling, given that the assumption of a purely homogeneous population cannot in general be seen to be valid. Two approaches have classically been used to address this problem; the use of deterministic segmentations of the population, and the use of a random continuous representation of variations in tastes across respondents. In this paper, a revised version of [10], we discuss an alternati

Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and Combinatorial Optimization based techniques. The key shortcomings of fitting based procedures include: a) synthesis of only one population, while there can be many populations matching the available data b) due to cloning rather than true synthesis of the

In this paper we propose the use of Discrete Choice Analysis (DCA) for static facial expression classification. Facial expressions are described with expression descriptive units (EDU), consisting in a set of high level features derived from an active appearance model (AAM). The discrete choice model (DCM) is built considering the 6 universal facial expressions plus the neutral one as the set of the available alternatives. Each alternative is described by an utility function, defined as the sum of a linear

We propose a new trust region based optimization algorithm for solving unconstrained nonlinear problems whose second derivatives matrix is singular at a local solution. We give a theoretical characterization of the singularity in this context and we propos ...

Disaggregated models, such as activity-based and random utility-based frameworks, play a central role in travel behaviour analysis and urban transport planning. However, conventional modelling practices often follow a sequential estimation-calibration process that introduces challenges such as error propagation, inconsistent value-of-time estimation, and poor alignment between micro-level behavioural outputs and macro-level system performance. This paper addresses these issues by proposing an integrated mod

Michel Bierlaire

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Modeling purchases of new cars: an analysis of the 2014 French market

Development of Prototype UrbanSim Models

The role of the social network and the usage of communication in travel behavior measured with Smartphone data

Network design of a transport system based on accelerating moving walkways

Discrete choice models with multiplicative error terms

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

Enumerative algorithms for choice-based pricing under capacity constraints

Capturing correlation in large-scale route choice models

A path choice approach to activity modeling with a pedestrian case study

Sampling of alternatives using multidimensional analysis

Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling

Association Generation in Synthetic Population for Transportation Applications: Graph-Theoretic Solution

A heuristic for nonlinear global optimization

Inventory routing with non-stationary stochastic demands

Overcapacity in European power systems: Analysis and robust optimization approach

Discrete mixture Models

Simulation based Synthesis of Population

Discrete Choice Models for Static Facial Expression Recognition

Dealing with singularities in nonlinear unconstrained optimization

Towards Unified Estimation and Calibration in Transport Models: Integrating Micro-level Behaviour and Macro-level Performance