Generalized Models of Sequential Decision-Making under Uncertainty

Sequential decision-making under uncertainty is an important branch of artificial intelligence research with a plethora of real-life applications. In this thesis, we generalize two fundamental properties of the decision-making process. First, we show that the theory on planning methods for finite spaces can be extended to infinite but countable...

Multi-Image Optimization based Specular Reflection Removal from Non-dielectric Surfaces

Specular light reflections are the mirror-like reflections from a material interface. They appear in the observation of any illuminated surface. Specular reflections can be set apart from the diffuse reflection type, which has a random distribution of reflection directions. The radiance of the specular reflected light is governed by the Fresnel...

NEO: NEuro-Inspired Optimization—A Fractional Time Series Approach

Solving optimization problems is a recurrent theme across different fields, including large-scale machine learning systems and deep learning. Often in practical applications, we encounter objective functions where the Hessian is ill-conditioned, which precludes us from using optimization algorithms utilizing second-order information. In this...

Optimizing Edge Computing in 5G Networks

Multi-access Edge Computing (MEC) is a concept brought up by ETSI and it places computing, storage, processing and network resources into MEC hosts and places these MEC hosts as close as needed to the telecom network edge in order to reduce service latency and bandwidth usage. For self-driving vehicles, streaming video and real-time gaming, the...

Infrastructure maintenance and replacement optimization under multiple uncertainties and managerial flexibility

Infrastructure maintenance and replacement decisions are subject to uncertainties such as regular asset degradation, structural failure, and price uncertainty. In the engineering domain, Markov Decision Processes (MDPs) typically focus on uncertainties regarding asset degradation and structural failure. While the literature in the engineering...

Port Call Efficiency Optimization, Using Data Analysis, Process Mining and Discrete Event Simulation

Port call efficiency (PCE) is an important factor in the port choice of shipping lines. This research strives to contribute to the current work on PCE optimization. This is done by applying relative new techniques on port call related data. A combination of process mining (PM) and discrete event simulation (DEVS) is explored, with the Port of...

LQG and Gaussian process techniques: For fixed-structure wind turbine control

Wind turbines are growing bigger to becomemore cost-efficient. This does increase the severity of the vibrations that are present in the turbine blades, both due to predictable effects like wind shear and tower shadow, and due to less predictable effects like turbulence and flutter. If wind turbines are to become bigger and more cost-efficient,...

Maintenance Optimization of Tidal Energy Arrays: Design of a Probabilistic Decision Support Tool for Optimizing the Maintenance Policy

The increasing demand for electricity offers many opportunities for renewable energy production, of which one alternative is tidal stream energy. Several feasibility studies have shown that the global tidal stream energy potential can contribute significantly to producing renewable energy. This tidal energy can mostly be produced at the 'tidal...

Parallel Approach to Derivative-Free Optimization: Implementing the DONE Algorithm on a GPU

Researchers at Delft University of Technology have recently developed an algorithm for optimizing noisy, expensive and possibly nonconvex objective functions for which no derivatives are available. The data-based online nonlinear extremum-seeker (DONE) was originally developed for sensorless wavefront aberration correction in optical coherence...

Artificial neural networks for determining the optimal process conditions of a gasification process

JAY: Kitting as optimization tool of aircraft maintenance

Kitting as (LEAN) method in handling and supplying material and tools is not used in the aircraft maintenance process of KLM. That was one of the researchers first findings when starting this study for KLM Royal Dutch airlines. Kitting is the gathering of components and parts needed for the manufacture of a particular assembly or product....

Optimized structural design of Plug & Play Core© modular stadia during preliminary design

Modular construction is the on-site assembly (installation and connection) of factory made units (Lawson et al., 2014). It allows fabrication of structural components to be moved from the building site to controlled environments. Ballast Nedam adopted modular construction as a key business strategy for the future (Ballast Nedam, 2014). Plug &...

Integrating Natural Ventilation within an optimization process of energy performance

Decisions made in the early stage of the design process can have huge impacts on the future performance of a building. The implementation of natural ventilation strategies should occur early in the design stages and it should be embedded into a multi-criteria optimization process in order to achieve low energy performance and indoor comfort.

Averaging Level Control to Reduce Off-Spec Material in a Continuous Pharmaceutical Pilot Plant

The judicious use of buffering capacity is important in the development of future continuous pharmaceutical manufacturing processes. The potential benefits are investigated of using optimal-averaging level control for tanks that have buffering capacity for a section of a continuous pharmaceutical pilot plant involving two crystallizers, a...

Sequential robust optimization of a V-bending process using numerical simulations

The coupling of finite element simulations to mathematical optimization techniques has contributed significantly to product improvements and cost reductions in the metal forming industries. The next challenge is to bridge the gap between deterministic optimization techniques and the industrial need for robustness. This paper introduces a...

Event-based progression detection strategies using scanning laser polarimetry images of the human retina

Monitoring glaucoma patients and ensuring optimal treatment requires accurate and precise detection of progression. Many glaucomatous progression detection strategies may be formulated for Scanning Laser Polarimetry (SLP) data of the local nerve fiber thickness. In this paper, several strategies, all based on repeated GDx VCC SLP measurements,...

Model reduction for dynamic real-time optimization of chemical processes

The value of models in process industries becomes apparent in practice and literature where numerous successful applications are reported. Process models are being used for optimal plant design, simulation studies, for off-line and online process optimization. For online optimization applications the computational load is a limiting factor. The...

Dynamic Optimization in Business-wide Process Control

The chemical marketplace is a global one with strong competition between man- ufacturers. To continuously meet the customer demands regarding product quality and delivery conditions without the need to maintain very large stor- age levels chemical manufactures need to strive for production on demand. In this thesis we research how market...