Simulated annealing

Formal sciences
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Mathematical optimization
Metaheuristics

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Optimum design of low environmental impact structures through component reuse

Jan Friedrich Georg Brütting

Load-bearing systems (structures) in buildings and infrastructure contribute to a significant share of adverse environmental impacts (EI) because of resource- and energy-intensive fabrication. A currently overlooked circular economy strategy to reduce EI i ...

EPFL2020

From Data to Decisions: Distributionally Robust Optimization is Optimal

Daniel Kuhn, Peyman Mohajerin Esfahani

We study stochastic programs where the decision-maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of independent samples from this distribution. In this setting, the goal is to find a procedure that transfo ...

2021

Dynamic Optimization of Reaction Systems via Exact Parsimonious Input Parameterization

Dominique Bonvin, Diogo Filipe Mateus Rodrigues

This paper discusses the use of parsimonious input parameterization for the dynamic optimization of reaction systems. This parameterization is able to represent the optimal inputs with only a few parameters. In the context of batch, semibatch, and continuo ...

AMER CHEMICAL SOC2019

Solar cooking potential in Switzerland: Nodal modelling and optimization

Andreas Schueler, Josef Andreas Schuler, Dasaraden Mauree, Olivia Valérie Charlotte Bouvard, Luc Burnier, Jérémy Jacques Antonin Fleury, Timothée Chatelain, Samson Taylor

Solar cooking is one possible solution to reduce the domination of fossil fuel in the domestic sector and to benefit from renewable energy. This study assesses the solar cooking potential in Switzerland. A nodal model, based on energy balance equations of ...

PERGAMON-ELSEVIER SCIENCE LTD2019

On reducing the number of decision variables for dynamic optimization

Dominique Bonvin, Diogo Filipe Mateus Rodrigues

This paper presents an input parameterization for dynamic optimization that allows reducing the number of decision variables compared to traditional direct methods. A small number of decision variables is likely to be beneficial for various applications su ...

2020

Large-scale variational inference for Bayesian joint regression modelling of high-dimensional genetic data

Hélène Ruffieux

Genetic association studies have become increasingly important in understanding the molecular bases of complex human traits. The specific analysis of intermediate molecular traits, via quantitative trait locus (QTL) studies, has recently received much atte ...

EPFL2019

Maximum-likelihood estimation of kinetic parameters via the extent-based incremental approach

Dominique Bonvin, Julien Léo Billeter, Diogo Filipe Mateus Rodrigues

For lumped homogeneous reaction systems, this paper presents a kinetic model identification scheme that provides maximum-likelihood parameter estimates and guarantees convergence to global optimality. The use of the extent-based incremental approach allows ...

PERGAMON-ELSEVIER SCIENCE LTD2019

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