Multi-period power utility optimization under stock return predictability

In this paper, we derive an analytical solution to the dynamic optimal portfolio choice problem in the case of an investor equipped with a power utility function of wealth. The results are established by solving the Bellman backward recursion under the assumption that the vector of asset returns follows a vector-autoregressive process with...

A machine learning approach for propeller design and optimization: Part II

We propose and analyse an optimization method that uses a machine learning approach to solve multi-objective, constrained propeller optimization problems. The method uses an online learning strategy where explainable supervised classifiers learn the location of the Pareto front and advise search strategies. The classifiers are trained with...

A machine learning approach for propeller design and optimization: Part I

This paper introduces a machine learning approach for optimizing propellers. The method aims to improve the computational cost of optimization by reducing the number of evaluations required to find solutions. This is achieved by directing the search towards design clusters with good performance, i.e. high propulsive efficiency and low...

A Markovian decision model of adaptive cancer treatment and quality of life

This paper develops and analyzes a Markov chain model for the treatment of cancer. Cancer therapy is modeled as the patient's Markov Decision Problem, with the objective of maximizing the patient's discounted expected quality of life years. Patients make decisions on the duration of therapy based on the progression of the disease as well as...

Integration of operation and design of solar fuel plants: A carbon dioxide to methanol case study

Operation and design of solar fuel plants involves a decision about the degree of coupling between the solar electricity profile and the plant. Full decoupling needs large scale battery storage to ensure power availability during the night while full coupling requires high conversion capacity during the day to realize the required average...

Dynamic optimization of ship energy efficiency considering time-varying environmental factors

Nowadays, optimization of ship energy efficiency attracts increasing attention in order to meet the requirement for energy conservation and emission reduction. Ship operation energy efficiency is significantly influenced by environmental factors such as wind speed and direction, water speed and depth. Owing to inherent time-variety and...

Development of a task-based design approach for solution crystallization processes

Crystallization is historically one of the most important separation and product formation technologies in chemical industry. The future impact of crystallization is expected to increase as new high-added value products are often in crystalline form and need to comply with increasingly stringent product quality requirements. This calls for...