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Related publications (27)

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Related publications (27)

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A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections

Michel Bierlaire

Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the last decade. Understanding the demand for these services is essential for planning and managing modern transportation systems. Existing studies develop statistical mod ...

2023

Modeling and mitigating supply chain disruptions as a bilevel network flow problem

Ralf Seifert, Anna Timonina-Farkas, René Yves Glogg

Years of globalization, outsourcing and cost cutting have increased supply chain vulnerability calling for more effective risk mitigation strategies. In our research, we analyze supply chain disruptions in a production setting. Using a bilevel optimization ...

2022

Optimal Matching of Random Parts

Thomas Alois Weber

This paper examines the minimization of the cost for an expected random production output, given an assembly of finished goods from two random inputs, matched in two categories. We describe the optimal input portfolio, first using the standard normal appro ...

2022

Hole transport material, synthesis thereof, and solar cell

Michael Graetzel, Shaik Mohammed Zakeeruddin, Yuhang Liu

The organic small molecule 4,4',4",4"'-(5,5-dimethoxycyclopenta-1,3-diene-1,2,3,4-tetrayl)tetrakis(N,N-bis(4-methoxyhenyl)aniline (CPDA 1), shows electrochemical properties very close to spiro-OMeTAD indicating a high compatibility with PSC systems for its ...

2022

Enabling renewable Europe through optimal design and operation

Alessio Santecchia

Europe is currently transitioning from fossil energy sources to renewable generation of electric power. Although fundamental to reach net-zero targets, intermittent renewables are disrupting conventional methods used in operational planning and design of p ...

EPFL2022

Memory of Motion for Initializing Optimization in Robotics

Teguh Santoso Lembono

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

EPFL2022

A note on universal inference

Anthony Christopher Davison, Timmy Rong Tian Tse

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

WILEY2022