Publications by Michel Bierlaire

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In recent years, interest in crowd dynamics and pedestrian modeling is reviving due to urban growth and its pressure on urban infrastructure. Crowd and pedestrian simulation is emerging as a tool for designing new infrastructures and optimizing the use of current infrastructures. Innovative data collection techniques and realistic experiments are vital in estimating the demand for these infrastructures. Our goal consists in first developing a methodology to collect data about activities, and then model the

Starting from the assumption of a future where the use of cars will be limited in dense urban areas, and thus streets could be used for innovative transport modes, this project investigates a system based on accelerated moving walkways (AMW). Differently from constant moving walkways, AMW can reach speeds up to 15km/h thanks to an acceleration section. This paper, after a review of existing AMW implementations, presents a description of this system and formulates an optimization problem to identify the opti

In airline scheduling problems, integrated decision methodologies have aroused intense interest in the last decade. These integrated approaches allow for more efficient solutions due to the simultaneous decision making process. The studied integrated models mostly consist of planning phase subproblems. However in order to be demand responsive, demand related information should also be included in planning models. For that matter supply-demand interactions are now being introduced in airline decision problem

We present behavioral models designed to capture the response of drivers to real-time traffic information. In 2003, we have conducted a survey in Switzerland in order to collect both Revealed Preferences (RP) and Stated Preferences (SP) about choice decisions in terms of route and mode. The RP data contains socioeconomic characteristics of the individuals in our samples, their actual usage of ITS as well as their actual route and mode choice behavior. The SP data provide us with stated route and mode choice

Determining appropriate utility specifications for discrete choice models is time-consuming and prone to errors. With the availability of larger and larger datasets, as the number of possible specifications exponentially grows with the number of variables ...

The integration of discrete choice models with Mixed Integer Linear Programming (MILP) models provides a better understanding of customers' preferences to operators while planning for their systems. However, the formulations associated with the former are highly nonlinear and non convex. To overcome this limitation, we propose a linear formulation of a general discrete choice model that can be embedded in any MILP model by relying on simulation. We characterize a demand-based benefit maximization problem to

Existing activity-based modeling predominantly focus on out-of-home activities in order to un- derstand transport demand. In this research, we extend the state of practice in activity-based modelling by determining both in- and out-of-home activities in a ...

This study presents a system dynamics framework that integrates transport and land use components internally, explicitly capturing their interrelations and model their evolution over time. The model operates at a discrete zonal scale with sub-annual time steps, enabling the representation of temporal lags at differing process speeds. A case study at a cross-national scale demonstrates the model’s ability to capture interregional dynamics, including commuting flows that span administrative borders —essential

In this paper, we consider the gate assignment for a large airline at its hub airport. It is considered to be a highly complex problem with the possibility of application in both planning as well as operations mode. There are various considerations that are involved while assigning gates to incoming and outgoing turns at an airport. Different gates have restrictions, such as adjacency, LIFO and push time, which is known in advance from the structure of the airport. When optimizing the assignment costs, we c

Oligopolistic competition occurs when a small number of operators compete for the same pool of customers. This is often the case in transportation, due to reasons such as external regulations, economies of scale and limited capacity of the infrastructure. ...

We propose an extension of secant methods for nonlinear equations using a population of previous iterates. Contrarily to classical secant methods, where exact interpolation is used, we prefer a least squares approach to calibrate the linear model. We propose an explicit control of the numerical stability of the method. We show that our approach can lead to an update formula. In that case, we prove the local convergence of the corresponding undamped quasi-Newton method. Finally, computational comparisons wit

Typical object 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. In general, ...

In this paper we extend the Multiple Indicator Solution (MIS) so that it can also be used to account for endogeneity when there are interactions between observed and unobserved factors in the specification of the utility function. We develop the theoretica ...

Discrete choice models are the state-of-the-art for the mathematical modeling of demand. Based on the concept of random utility, they are able to predict the choice behavior of individuals. However, these models are highly non linear and non convex in the variables of interest, and therefore difficult to be included in mixed linear optimization models. Furthermore, these models are of great importance in transportation revenue management systems. In this research, we propose a new mathematical modeling fram

In this paper, we consider the recovery of an airline schedule after an unforeseen event called disruption, making the planned schedule infeasible. We present a modeling framework that allows the consideration of operational constraints within a Column Gen ...

In this paper, we present a novel activity-based scheduling model that combines a continuous optimisation framework for temporal scheduling decisions (i.e. activity timings and durations) with traditional discrete choice models for non-temporal choice dimensions (i.e. activity participation, number and type of tours, and considered destinations). The central concept of our approach is that individuals resolve time conflicts that arise from overlapping activities, e.g. needing to work and desiring to shop at

Analytic queueing network models often assume infinite capacity for all queues. For real systems this infinite capacity assumption does not hold, but is often maintained due to the difficulty of grasping the between-queue correlation structure present in finite capacity networks. This correlation structure helps explain bottleneck effects and spillbacks, the latter being of special interest in networks containing loops because they are a source of potential deadlock. We present an analytic queueing network

Discrete choice models are the state-of-the-art of demand modeling at the disaggregate level. Their integration with Mixed Integer Linear Programming (MILP) models provides a better understanding of customers' preferences to operators while planning for their systems. However, the formulations associated with discrete choice models are highly nonlinear and non convex, and therefore difficult to include in MILP models. In order to overcome this limitation, we propose a linear formulation of a general discret

BIOGEME is a free software package for estimating by maximum likelihood a broad range of random utility models. It can estimate particularly Multivariate Extreme Value (MEV) models including the logit model, the nested logit model, the cross-nested logit model, and the network MEV model, as well as continuous and discrete mixtures of these models. Biogeme has been designed to provide modelers with tools to investigate a wide variety of discrete choice models without worrying about the estimation algorithm i

This paper proposes a mathematical framework that provides the detailed characterization of the pedestrian flow. It is specifically designed to address the heterogeneity of pedestrian population which is to be reflected through the pedestrian flow indicators. The key components of the presented work are: (i) data driven space discretization framework based on the Voronoi tessellations that allow pedestrian-oriented definition of density indicator; (ii) statistical and data driven approach to time aggregatio

Michel Bierlaire

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A Bayesian Approach to Detect Pedestrian Destination-Sequences from WiFi Signatures

Optimization of the network design of a futuristic transport system based on moving walkways

Integration of explicit supply-demand interactions in airline schedule planning and fleet assignment

Analysis of driver's response to real-time information in Switzerland

Assisted specification of discrete choice models

A Lagrangian relaxation technique for the demand-based benefit maximization problem

A utility optimization-based framework for joint in- and out-of-home scheduling

A Cross-Border Dynamic Land Use–Transport Model: Integrating Housing and Commuting in Luxembourg

Multi-Objective Airport Gate Assignment Problem

A demand-based optimization approach to find market equilibria in oligopolies

A multi-iterate method to solve systems of nonlinear equations

A Master-Slave Approach for Object Detection and Matching with Fixed and Mobile Cameras

Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data

A new mathematical representation of demand using choice-based optimization method

Constraint-specific recovery networks for solving airline recovery problems

Resolving time conflicts in activity-based scheduling

An analytic finite capacity queueing network model capturing blocking, congestion and spillbacks

A Lagrangian relaxation technique for the demand-based benefit maximization problem

Estimation of discrete choice models: extending BIOGEME

Probabilistic speed-density relationship for pedestrians based on data driven space and time representation