Publications by Michel Bierlaire

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Pedestrian detection in the surroundings of a vehicle is highly desirable to avoid dangerous traffic situations. Typical vision-based pedestrian detection algorithms on mobile cameras suffer from the lack of a-priori knowledge on the object to be detected. The variability in the shape, pose, color distribution, and behavior affect the robustness of the detection process. A novel vision-based system is proposed to detect pedestrians with a single mobile camera collaborating with a fixed camera observing the

Attitudinal attributes play an important role in behavior of individuals in various contexts. In this study we focus on the travel behavior and our main objective is to come up with segments of individuals that have different mode choice preferences with the help of the attitudinal attributes. These segments are important for the design of more efficient public transport policies specific to the characteristics of different customers. In order to identify the segments of individuals, most importantly the po

The integration of discrete choice models in optimization is appealing to operators and policy makers (the supply) because it provides a better understanding of the preferences of clients (the demand) while planning for their systems. Notwithstanding the clear advantages, the complexity of discrete choice models leads to mathematical formulations that are highly nonlinear and nonconvex in the variables of interest, and therefore difficult to be included in mixed integer linear problems (MILP), which are the

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 base ...

In freight railway networks, commodities are usually transported via hubs, which are called marshaling or shunting yards, depending on their capacity. Consequently, the number and locations of these yards effect the transport costs to a great extent. The goal of our work is to reduce the freight transport and yard operation costs by determining the optimal number and locations of the yards. Therefore, we have defined an optimization problem, which integrates the hub location and multicommodity network desig

Discrete choice models are defined conditional to the analyst's knowledge of the actual choice set. The common practice for many years has been to assume that individual-based choice sets can be deterministically generated on the basis of the choice contex ...

The vehicle sharing systems (VSSs) are becoming more and 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, imbalance of the vehicles, ...

Facial expression recognition by human observers is affected by subjective components. Indeed there is no ground truth. We have developed Discrete Choice Models (DCM) to capture the human perception of facial expressions. In a first step, the static case is treated, that is modelling perception of facial images. Image information is extracted using a computer vision tool called Active Appearance Model (AAM). DCMs attributes are based on the Facial Action Coding System (FACS), Expression Descriptive Units (E

In this paper we aim at integrating the selection of a nesting structure to the maximum likelihood framework of the parameter estimation. Given a finite set of nesting structures, the traditional approach is to estimate the models corresponding to each of them and select a posteriori the most appropriate one based on some fit statistics and informal testing procedures. However, the number of possible nesting structures grows as a function of the number of alternatives. Our approach simultaneously solves the

A method is proposed to probabilistically map location observations to the underlying network. Instead of generating a single path as the map matching algorithms do, this method aims at calculating a likelihood for each potentially true path to have been the actual path. The result can be used in route choice modeling to avoid biases introduced by a deterministic map matching algorithm. Both spatial and temporal relationships existing in the location data trace and network are taken into account in the meth

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

In this paper we study the simultaneous optimization of berth allocation and quay crane assignment in seaport container terminals. We propose a model based on an exponential number of variables that is solved via column generation. An exact branch and pric ...

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. In general, the universe of RUM consistent models is much larger, ...

We present a spatial Branch and Bound and spatial Branch and Benders Decomposition approach together with the Breakpoint Exact Algorithm (BEA) to tackle the uncapacitated choice-based pricing problem (CPP) where demand is captured by a discrete choice model (DCM) based on the random utility principle. We leverage problem characteristics to reformulate the state-of-the-art simulation-based formulation of the CPP as a mixed-integer linear program (MILP) into a non-convex quadratically constrained quadratic pr

We consider the previously unsolved problem of sampling paths according to a given distribution from a general network. The problem is difficult because of the combinatorial number of alternatives, which prohibits a complete enumeration of all paths and he ...

We first review the impact of various sampling strategies on the estimation of discrete choice models. In particular, consistent estimates of all parameters of a multinomial logit (MNL) model, except the constants, can be obtained from an exogenous sample maximum likelihood (ESML) estimation in the presence of choice-based sampling strategies. Then, we describe the recent estimator proposed by Bierlaire, Bolduc and McFadden (2008) [The estimation of Generalized Extreme Value models from choice-based samples

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

The use of discrete choice models (DCMs) is a regular approach to investigating migration aspirations concerning destination choices. However, given the complex substitution patterns between destinations, more advanced model specifications than the multino ...

We present a framework for estimating pedestrian demand within a train station. It takes into account ridership data, and various direct and indirect indicators of demand. Such indicators may include link flow counts, density measurements, survey data, his ...

The choice of a specific distribution for random parameters of discrete choice models is a critical issue in transportation analysis. Indeed, various pieces of research have demonstrated that an inappropriate choice of the distribution may lead to serious ...

Michel Bierlaire

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Combination of Fixed and Mobile Cameras for Automatic Pedestrian Detection

Mode choice with attitudinal latent class: a Swiss case-study

Integrating advanced discrete choice models in mixed integer linear optimization

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

Freight railway network design problem

An analysis of the implicit choice set generation using the Constrained Multinomial Logit model

An optimization framework for a light electric vehicle sharing system

Capturing Human Perception of Facial Expressions by Discrete Choice Modelling

Discrete-continuous maximum likelihood for the estimation of nested logit models

A method of calculating path observation likelihood from GPS data

A heuristic for nonlinear global optimization

An exact algorithm for the integrated planning of berth allocation and quay crane assignment

Discrete choice models with multiplicative error terms

Exact algorithms for continuous pricing with advanced discrete choice demand models

Metropolis-Hastings sampling of paths

Estimation of discrete choice models under various sampling strategies

Two-stage column generation and applications in container terminal management

Sampling of alternatives in migration aspiration models

Estimation of pedestrian origin-destination demand in train stations

A practical test for the choice of mixing distribution in discrete choice models