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Combinatorial Optimization for Behavioral Response Analysis

Objective

In the evolving mobility landscape, travel demand models are crucial
for public authorities, consulting firms, or transportation
operators. These tools are indispensable for developing and managing
the transportation systems of the future. Built on choice models, they
predict a wide range of traveling decisions. Current models face
challenges in (i) enumerating all alternatives and (ii) implicitly
treating constraints. Combinatorial by nature, travel decisions
involve a huge number of alternatives, and are more often influenced
by constraints than preferences.

At a time where most trips are made for leisure, the
behavior of social groups such as families, friends, and colleagues
plays a major and complex role. Also, analyzing behavior over time is
essential because of the significant role played by learning, habits
and inertia.

The key idea of this project is to bypass the need for explicit
enumeration of alternatives by representing constraints directly
through combinatorial optimization. This methodological shift enables
the development of a new generation of travel demand models that embed
the full richness of advanced discrete choice frameworks. In
particular, the proposed approach will incorporate latent variables to
capture complex behavioral dimensions such as social norms, habitual
behavior, bounded rationality, and equity concerns. By explicitly
integrating cutting-edge operations research techniques with
behaviorally informed modeling, the project paves the way for
scalable, realistic, and theory-driven simulations of individual and
group travel decisions across time.

Our research objectives are to: validate and operationalize
combinatorial choice models; enhance their scalability through
advanced optimization and simulation methods; investigate their
capacity to capture behavioral dynamics and social influences; and
assess their significant potential for applications beyond travel
demand modeling.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2025-ADG

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Host institution

ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 497 220,00
Address
BATIMENT CE 3316 STATION 1
1015 Lausanne
Switzerland

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Region
Schweiz/Suisse/Svizzera Région lémanique Vaud
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data

Beneficiaries (1)