An optimum design course is being taught to undergraduate students as a basic discipline in engineering and technology education. Optimum design aims primarily at determining the best possible combination of solutions used as design parameters to maximise or minimise an optimisation problem. The development of conventional optimum approaches has dramatically influenced modern teaching technolog...

In many application domains, optimisation, decision analysis and other analytic models are often embedded as a decision engine within the respective business processes. In order to respond effectively to global as well as regional competition, successful companies have started to formalise and improve their Business Process Management (BPM) procedures. In this paper, we study recent trends in t...

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...

A broadband Circuit Analogue (CA) absorber using double-circular-loop array is investigated in this paper. A simple equivalent circuit model is presented to accurately analyze this CA absorber. The circuit simulation of the proposed model agrees well with full-wave simulations. Optimization based the equivalent circuit model, is applied to design a single-layer circuit analogue absorber using d...

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...