This thesis elucidates the distinctions between the population-based and the island-based approach. These approaches differ in terms of whether the individuals are part of a single population or...

Climate Change is real, and this has been affecting the weather all around the world. With weather conditions changing, this thesis aims to understand how weather can be used to forecast market...

This work presents a solution to the unit commitment problem (UCP) in energy grid management, an optimization problem that involves solving a system of equations to calculate costs for a given...

Switching to 100 % renewable energy production is one of the most important steps societies are currently taking in combating the climate crisis. This switch however requires new techniques for the...

Quantum Reinforcement Learning offers the potential for advantages over classical Reinforcement Learning, such as a more compact representation of the state space through quantum states. Furthermore,...

Quantum computing, a discipline that leverages the principles of quantum physics to perform complex calculations, has emerged as a transformative field since its initial conceptualization by Richard...

In practice, a quantum computer, like a classical computer, has only a limited set of operations. These operations, called quantum gates, are modelled by unitary transformations according to the...

Quantum computing is an emerging technology that can potentially improve different tasks in machine learning. Combining the representational power of a classically hard quantum kernel and the...

Currently, we are in the Noisy Intermediate Scale Quantum (NISQ) era, where the number of qubits that can be used in a single quantum computer is increasing. However, with this development come...

An important optimization problem in computer science is the detection of communities. By analyzing networks, so-called communities can be found and important information in many fields - from...