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Passenger-centric timetable rescheduling: A user equilibrium approach

Publications associées (32)

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Hardware-Software co-design Methodologies for Edge AI Optimization

Flavio Ponzina

ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...

EPFL2023

Stochastic adaptive resampling for the estimation of discrete choice models

Michel Bierlaire, Nicola Marco Ortelli, Matthieu Marie Cochon de Lapparent

In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

2023

This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions ...

Oxford2023

Machine learning methods to assist energy system optimization

Jean-Louis Scartezzini, Amarasinghage Tharindu Dasun Perera, Vahid Moussavi Nik

This study evaluates the potential of supervised and transfer learning techniques to assist energy system optimization. A surrogate model is developed with the support of a supervised learning technique (by using artificial neural network) in order to bypa ...

2019

Exploiting structure of chance constrained programs via submodularity

Maryam Kamgarpour, Tony Alan Wood

We introduce a novel approach to reduce the computational effort of solving convex chance constrained programs through the scenario approach. Instead of reducing the number of required scenarios, we directly minimize the computational cost of the scenario ...

2019

Robust multi-objective optimization of solid oxide fuel cell–gas turbine hybrid cycle and uncertainty analysis

François Maréchal, Shivom Sharma

Chemical process optimization problems often have multiple and conflicting objectives, such as capital cost, operating cost, production cost, profit, energy consumptions and environmental impacts. In such cases, Multi-Objective Optimization (MOO) is suitab ...

2018

Nature has the ability to cope with extreme pH, temperature and pressure, in addition to bestowing a wide array of functionalities to (bio)macromolecules. These specialized skills have attracted the interest of vast scientific communities especially in vie ...

EPFL2018

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Compressed air energy storage technologies can improve the supply capacity and stability of the electric- ity grid, particularly when fluctuating renewable energies are massively connected. While incorporating the combined cooling, heating and power system ...

2017

A Multilevel Monte Carlo Evolutionary Algorithm for Robust Aerodynamic Shape Design

Fabio Nobile, Pénélope Leyland, Michele Pisaroni

The majority of problems in aircraft production and operation require decisions made in the presence of uncertainty. For this reason aerodynamic designs obtained with traditional deterministic optimization techniques seeking only optimality in a specific s ...

2017

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Biomimicry is a strategy that makes practical use of evolution to find efficient and sustainable ways to produce chemical compounds or engineer products. Exploring the natural machinery of enzymes for the production of desired compounds is a highly profita ...

2016