Publications associées à Optimization Methodology of Dynamic Data Structures Based on Genetic Algorithms for Multimedia Embedded Systems

Automated Formal Verification of Software Network Functions

Formally verifying the correctness of software is necessary to merit the trust people put in software systems. Currently, formal verification requires human effort to prove that a piece of code matches its specification and code changes to improve verifiab ...

EPFL2024

A ride time-oriented scheduling algorithm for dial-a-ride problems

Nikolaos Geroliminis, Claudia Bongiovanni, Mor Kaspi

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Pergamon-Elsevier Science Ltd2024

Data from: Optimal blade pitch control for enhanced vertical-axis wind turbine performance

Sébastien Le Fouest, Karen Ann J Mulleners

This directory contains open-source data obtained using a single-bladed H-type vertical-axis wind turbine prototype with individual blade pitching. This data results from the optimisation of the blade's pitching kinematics using a genetic algorithm at two ...

Zenodo2024

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Siang-Yun Lee

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

EPFL2024

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

Pascal Fua, Zhen Wei

Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...

2024

Design and in vitro Characterization of a Wearable Multisensing System for Hydration Monitoring

Sandro Carrara, Sarah Tonello, Ata Jedari Golparvar, Ali Meimandi

Dehydration is a frequent condition in the elderly and can lead to serious health complications if not compensated timely. Early diagnosis can be problematic, as medical examinations in the hospital would be needed. Fully wearable low-cost multisensing dev ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Mesh-based topology, shape and sizing optimization of ribbed plates

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

Springer2024

COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

Laura Grigori

Multiple tensor-times-matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimensional data analysis. We establish communication lower bounds that determine ...

Siam Publications2024

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

François Maréchal, Julia Granacher

In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...

Pergamon-Elsevier Science Ltd2023

Genetic Algorithms for the Discovery of Homogeneous Catalysts

Anne-Clémence Corminboeuf, Puck Elisabeth van Gerwen, Simone Gallarati, Rubén Laplaza Solanas, Alexandre Alain Schöpfer

In this account, we discuss the use of genetic algorithms in the inverse design process of homogeneous catalysts for chemical transformations. We describe the main components of evolutionary experiments, specifically the nature of the fitness function to o ...

2023

Fast correlation function calculator A high-performance pair-counting toolkit

Cheng Zhao

Context. A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented.Aims. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simula ...

EDP SCIENCES S A2023

Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm

Fernando Porté Agel, Nicolas Otto Kirchner Bossi

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 ...

Pergamon-Elsevier Science Ltd2023

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Pascal Frossard, Roberto Gerson De Albuquerque Azevedo, Chaofan He

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Optimization of elastic wave propagation in a reconfigurable medium by genetic algorithms with adaptive mutation probability

Romain Christophe Rémy Fleury, Janez Rus

We introduce a reconfigurable medium for the manipulation of elastic propagation properties of Lamb waves. It is based on a shape memory polymer (SMP) with temperature-dependent Young's modulus. Waves are excited by a laser pulse and detected by a laser vi ...

IOP Publishing Ltd2023

Stochastic-robust planning optimization method based on tracking-economy extreme scenario tradeoff for CCHP multi-energy system

François Maréchal, Yuxuan Li

The load tracking performance of combined cooling, heating, and power multi-energy system (CCHP-MES) greatly depends on the equipment capacity configuration. And the frequent fluctuations in the source-load uncertainty puts higher demands on the load track ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Computational conceptual design — typological exploration of spatial truss systems through optimization

Corentin Jean Dominique Fivet, Jonas Warmuth, Pierluigi D'Acunto

Exploring a wide range of design options is crucial for every sound conceptual design process. In the conventional structural design workflow, optimization techniques are generally employed to generate well-performing design options. However, focusing only ...

International Association for Shell and Spatial Structures (IASS)2023

Modeling and Design Optimization of Loosely Coupled PCB Spiral Coils in Inductive Power Transfer Systems

Drazen Dujic, Xiaotong Du

There are various possibilities to realize coil winding designs for an inductive power transfer system. In order to achieve high power transfer efficiency and power density and explore trade-offs between the two, design optimization around the coil link is ...

2023

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

Sayan Ghosh, Chao Hu, Olga Fink

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...

SPRINGER2023