The complexity of chemical plant systems (CPS) makes optimising their design and
operation challenging tasks. This complexity also results in analytical and numerical …

Portfolio management is a multi-period multi-objective optimisation problem subject to
various constraints. However, portfolio management is treated as a single-period problem …

State-of-the-art RL algorithms have shown suboptimal performance in some market
conditions with regard to the portfolio selection problem. The reason for suboptimal …

The fusion of public sentiment data in the form of text with stock price prediction is a topic of
increasing interest within the financial community. However, the research literature seldom …

Cryptocurrencies are peer-to-peer digital assets monitored and organised by a blockchain
network. Price prediction has been a significant focus point with various machine learning …

Multi-objective portfolio optimisation is a critical problem researched across various fields of
study as it achieves the objective of maximising the expected return while minimising the risk …

We present the constrained portfolio selection problem as a learning problem requiring
hyper-parameter specification. In practice, hyper-parameters are typically selected using a …

Technology has transformed nearly every field. Financial analysts are using FinTech for
collecting data, extracting valuable insights, making predictions. The paper explores …

Real-world optimisation problems typically have objective functions which cannot be
expressed analytically. These optimisation problems are evaluated through expensive …

Portfolio management is a multi-period multi-objective optimization problem subject to a
wide range of constraints. However, in practice, portfolio management is treated as a single …