Integer traffic assignment problem: Algorithms and insights on random graphs

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The chemical industry faces mounting pressure to develop more sustainable processes while accelerating innovation to address climate challenges. Traditional discovery approaches in chemistry follow an iterative cycle: forming hypotheses about new molecules ...

This thesis contributes to the modelling of multivariate rare events by combining extreme value theory and graphical modelling. The central theme involves structural equation models (SEMs), which are powerful tools used to express causal extremal dependenc ...

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

This work proposes the extended functional tensor train (EFTT) format for compressing and working with multivariate functions on tensor product domains. Our compression algorithm combines tensorized Chebyshev interpolation with a low-rank approximation alg ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome densities, ...

In this paper, three machine learning (ML)-based approaches—XGBoost, Artificial Neural Network (ANN), and Random Forest algorithms—are compared for the localization of lightning through the analysis of lightninginduced voltages on power transmission lines. ...

This study proposes a multi-objective optimization methodology for planning multi-energy complementary distributed energy systems considering process synergy and thermal integration. The process integration tech-nique is integrated into the Energy Hub mode ...

Choice-based optimization problems are the family of optimization problems that incorporate the stochasticity of individual preferences according to discrete choice models to make planning decisions. This integration brings non-convexity and nonlinearity t ...

Carpooling is an efficient measure to fight car ownership and reduce vehicle kilometres travelled. By individuals sharing their commutes, vehicle occupancy increases and congestion is reduced. We develop a dynamic ADL (Arnott, de Palma, Lindsey)-Vickrey ap ...

This article proposes a new logic synthesis and verification paradigm based on circuit simulation. In this paradigm, high quality, expressive simulation patterns are pregenerated to be reused in multiple runs of optimization and verification algorithms, re ...

The performance of some emerging nanotechnolo- gies benefits from wave pipelining. The design of such circuits re- quires new models and algorithms. Thus we show how Majority- Inverter Graphs (MIG) can be used for this purpose and we extend the related opt ...

Computational micromechanics and homogenization require the solution of the mechanical equilibrium of a periodic cell that comprises a (generally complex) microstructure. Techniques that apply the Fast Fourier Transform have attracted much attention as the ...

Path-following tasks, which refer to dynamic motion planning along pre-specified geometric references, are frequently encountered in applications such as milling, robot-supported measurements, and trajectory planning for autonomous vehicles. Different conv ...

Congestion is a phenomenon that arises in a variety of contexts. The most familiar representation is urban traffic congestion. Nonetheless, phenomenons such as prison cell congestion, hospital bed blocking or, at a cellular scale, ribosome congestion, also ...

This thesis proposes novel ways both to represent the static surfaces, and to parameterize their deformations. This can be used both by automated algorithms for efficient 3–D shape reconstruction, and by graphics designers for editing and animation. Deform ...

Integer traffic assignment problem: Algorithms and insights on random graphs

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Integrating AI across the Chemistry Discovery Cycle: Advancing Sustainable Chemistry through Digital Methods

Structural equation models for multivariate extremes

Learning to Remove Cuts in Integer Linear Programming

Approximation in the extended functional tensor train format

Machine learning-aided generative molecular design

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

An Efficient Machine Learning Model for Lightning Localization via Lightning-Induced Voltages on Transmission Lines

A multi-objective planning method for multi-energy complementary distributed energy system: Tackling thermal integration and process synergy

A Lagrangian decomposition scheme for choice-based optimization

Influence of dynamic congestion with scheduling preferences on carpooling matching with heterogeneous users

A Simulation-Guided Paradigm for Logic Synthesis and Verification

Wave Pipelining for Majority-based Beyond-CMOS Technologies

Finite strain FFT-based non-linear solvers made simple

Time-Optimal Path-Following Operation in the Presence of Uncertainty

Mitigating network congestion : analytical models, optimization methods and their applications

Addendum to "Bicolored matchings in some classes of graphs"

Control and Optimization of Batch Processes: Improvement of Process Operation in the Production of Specialty Chemicals

Implicit meshes : unifying implicit and explicit surface representations for 3D reconstruction and tracking