118 zoekresultaten voor “optimization” in de Publieke website
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Benchmarking Discrete Optimization Heuristics
This thesis involves three topics: benchmarking discrete optimization algorithms, empirical analyses of evolutionary computation, and automatic algorithm configuration.
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Many objective optimization and complex network analysis
This thesis seeks to combine two different research topics; Multi-Objective Optimization and Complex Network Analysis.
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Data Driven Modeling & Optimization of Industrial Processes
Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.
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Self-Adjusting Surrogate-Assisted Optimization Techniques for Expensive Constrained Black Box ProblemsBagheri, S.
Optimization tasks in practice have multifaceted challenges as they are often black box, subject to multiple equality and inequality constraints and expensive to evaluate.
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A versatile tuple-based optimization framework
Promotor: Prof.dr. H.A.G. Wijshoff
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weighted ensembles of surrogate models for sequential parameter optimization
It is a common technique in global optimization with expensive black-box functions to learn a surrogate-model of the response function from past evaluations and use it to decide on the location of future evaluations.
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Optimization of quantum algorithms for near-term quantum computers
This thesis covers several aspects of quantum algorithms for near-term quantum computers and its applications to quantum chemistry and material science.
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Evolutionary Multi-Criterion Optimization (EMO) conference
Congres/symposium
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Stochastic and Deterministic Algorithms for Continuous Black-Box Optimization
Continuous optimization is never easy: the exact solution is always a luxury demand and the theory of it is not always analytical and elegant.
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Designing Ships using Constrained Multi-Objective Efficient Global Optimization
A modern ship design process is subject to a wide variety of constraints such as safety constraints, regulations, and physical constraints.
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Multi-Objective Bayesian Global Optimization for Continuous Problems and Applications
A common method to solve expensive function evaluation problem is using Bayesian Global Optimization, instead of Evolutionary Algorithms.
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Estimation and Optimization of the Performance of Polyhedral Process Networks
Promotor: Prof.dr.ir. E. Deprettere
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Dynamic real-time substrate feed optimization of anaerobic co-digestion plants
Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M. Bongards (Cologne University)
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Quality-driven multi-objective optimization of software architecture design: method, tool, and application
Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M.R.V. Chaudron, Co-Promotor: M.T.M. Emmerich
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Representations of High-dimensional CAE Models for Automotive Design Optimization
In design optimization problems, engineers typically handcraft design representations based on personal expertise, which leaves a fingerprint of the user experience in the optimization data. Thus, learning this notion of experience as transferrable design features has potential to improve the performance…
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Generalized Strictly Periodic Scheduling Analysis, Resource Optimization, and Implementation of Adaptive Streaming Applications
This thesis focuses on addressing four research problems in designing embedded streaming systems.
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Small changes for long term impact: optimization of structure kinetic properties: a case of CCR2 antagonists
Promotor: Prof.dr. A. P. IJzerman, Co-Promotor: L.H. Heitman
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Data-Driven Machine Learning and Optimization Pipelines for Real- World Applications
Machine Learning is becoming a more and more substantial technology for industry.
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Advances in computational methods for Quantum Field Theory calculations
In this work we describe three methods to improve the performance of Quantum Field Theory calculations.
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The Many Faces Of Online Learning
In this dissertation several settings in the Online Learning framework are studied. The first chapter serves as an introduction to the relevant settings in Online Learning and in the subsequent chapters new results and insights are given for both full-information and bandit information settings.
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Novel approaches for direct exoplanet imaging: theory, simulations and experiments
The next generation of high-contrast imaging instruments on space-based observatories requires sophisticated wavefront sensing and control in addition to a high-performance coronagraph.
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Yingjie Fan
Wiskunde en Natuurwetenschappen
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Oscar Rueda
Wiskunde en Natuurwetenschappen
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Guiding evolutionary search towards innovative solutions
Promotors: Prof.dr. T.H.W. Bäck, Prof.dr. B. Sendhoff (Technische Universität Darmstadt)
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Controlling growth and morphogenesis of the industrial enzyme producer Streptomyces lividans
Promotor: G.P. van Wezel, Co-Promotor: E. Vijgenboom
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CIMPLO – Onderhoud voor industrieën voorspellen
Onderzoekers van het Leiden Institute of Advanced Computer Science (LIACS) ontwikkelen een systeem dat automatisch waarschuwingen uitstuurt wanneer onderdelen van motoren de eerste verschijnselen van vermoeidheid beginnen te vertonen. Het project duurt 4 jaar.
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Strategies for Mechanical Metamaterial Design
On a structural level, the properties featured by a majority of mechanical metamaterials can be ascribed to the finite number of soft internal degrees-of freedom allowing for low-energy deformations.
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Jana Enking
Wiskunde en Natuurwetenschappen
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Guilherme Perin
Wiskunde en Natuurwetenschappen
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Bartolomeus Häussling Löwgren
Wiskunde en Natuurwetenschappen
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Benchmarking Discrete Optimization Heuristics
Promotie
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Thomas Bäck
Wiskunde en Natuurwetenschappen
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Applications of quantum annealing in combinatorial optimization
Promotie
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Many Objective Optimization and Complex Network Analysis
Promotie
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Data Driven Modeling & Optimization of Industrial Processes
Promotie
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Statisticus Heike Trautmann is Pascalhoogleraar 2017
De Duitse hoogleraar Information Systems and Statistics Heike Trautmann aanvaardde deze maand de Pascalleerstoel bij LIACS, het informatica-instituut aan de Universiteit Leiden. Trautmanns belangrijkste vakgebieden zijn evolutionary multiobjective optimisation en data science, waar ook LIACS sterk in…
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Sparsity-Based Algorithms for Inverse Problems
Inverse problems are problems where we want to estimate the values of certain parameters of a system given observations of the system. Such problems occur in several areas of science and engineering. Inverse problems are often ill-posed, which means that the observations of the system do not uniquely…
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LeGO 2018: 14th International Workshop on Global Optimization
Congres/symposium
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Morphogenesis and protein production in Aspergillus niger
Promotores: C.A.M.J.J. van den Hondel, V. Meyer, Co-promotor: A.F.J. Ram
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Illuminating N-acylethanolamine biosynthesis with new chemical tools
In this thesis, the discovery and optimization is described of chemical tools to study the N-acylethanolamine (NAE) biosynthetic pathway.
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Discovering the preference hypervolume: an interactive model for real world computational co-creativity
In this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance introverted intuition using extraverted intuition's communication lines.
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Optimization of quantum algorithms for near-term quantum computers
Promotie
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weighted ensembles of surrogate models for sequential parameter optimization
Promotie
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Stochastic and Deterministic Algorithms for Continuous Black-Box Optimization
Promotie
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Optimization and Application of 3D Reconstruction for Optical Projection Tomography
Promotie
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Multi-objective Evolutionary Algorithms for Optimal Scheduling
Multi-criteria optimalisatie is een effectieve techniek voor het vinden van optimale oplossingen die een afweging bieden tussen verschillende, tegenstrijdige criteria. Het heeft zijn toepassing gevonden in de wereld om ons heen omdat bij het oplossen van praktische, re¨ele wereld problemen men gewoonlijk…
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Searching by Learning: Exploring Artificial General Intelligence on Small Board Games by Deep Reinforcement Learning
In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…
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The electrode-electrolyte interface in CO2 reduction and H2 evolution: a multiscale approach
Electrocatalysis allows for storing electricity or converting it into chemical bonds, producing chemical building blocks and fuels using renewable resources.
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Improving robustness of tomographic reconstruction methods
Promotor: Prof.dr. K.J. Batenburg
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Photothermal studies of single molecules and gold nanoparticles: vapor nanobubbles and conjugated polymers
Promotor: M.A.G.J. Orrit