This paper describes an experiment to test the performance of Kriging surrogate modelling optimisation techniques on a building design problem with discrete design choices. Surrogate modelling optimisation offers advantages over traditional optimisation techniques on design problems with expensive (time consuming) performance evaluation models. The techniques are tested for both single and mult...

In recent years, vector optimisation with set-valued maps in infinite dimensional spaces has been received an increasing amount of attention. See [6, 2, 5, 8, 4, 9] and references therein, for its extensive applications in many fields such as mathematical programming, optimal control, management science. Vector optimisation with setvalued maps, sometimes called set-valued vector optimisation fo...

Abstract Optimisation algorithms such as the Newton method were first generalised to manifolds by generalising components of algorithm directly: gradients replaced Riemannian gradients, straight lines geodesics, and so forth. This meant having endow manifold with a metric. Traditionally then, attention focused on geometry underlying manifold. However, we argue is not right focus because it does...

Ontologies describe real-world entities in terms of axioms, i.e. statements about them, and have become an established instrument for formally modelling and representing knowledge. The diversity of available ontologies results in a heterogeneous landscape where ontologies can overlap in their content. Such an overlap can be caused by ontologies modelling the same or similar domains created by d...

The current state of traditional software development is surveyed and essential problems are investigated on the basis of system theoretical considerations. The concept of optimisation cycle is proposed as a solution. The relation of several different kinds of local optimisation cycles to the specifications, the communications, and the optimisation barrier is integrated into a concept of partic...

Interactive Multi-Objective Optimisation is an increasing field of evolutionary and swarm intelligence-based algorithms. By involving a human decision, a set of relevant non-dominated points can often be acquired at significantly lower computational costs than with a posteriori algorithms. A rarely addressed issue in interactive optimisation is the design of efficient user interfaces and the ap...

We present an efficient block-diagonal approximation to the Gauss-Newton matrix for feedforward neural networks. Our resulting algorithm is competitive against state-of-the-art first-order optimisation methods, with sometimes significant improvement in optimisation performance. Unlike first-order methods, for which hyperparameter tuning of the optimisation parameters is often a laborious proces...