In this work, we present a new algorithm for solving complex multi-stage optimisation problems involving hard constraints and uncertainties, based on dynamic and multi-parametric programming. Each echelon of the dynamic programming procedure, typically employed in the context of multi-stage optimisation models, is interpreted as a robust multi-parametric optimisation problem, with the present s...

This master thesis presents an ant colony optimisation algorithm for the bounded diameter minimum spanning tree problem, a NP-hard combinatorial optimisation problem with various application fields, e.g. when considering certain aspects of quality in communication network design. The algorithm is extended with local optimisation in terms of a variable neighbourhood descent algorithm based on fo...

PLATON is a Problem Solving Environment (PSE) for distributed numerical optimisation that allows the construction and steering of large-scale optimisation processes on a computational Grid. It is also an environment for coupling optimisation and simulation software. Evolutionary Optimisation is a good example of a problem which can efficiently designed to run in a Grid environment. After a shor...

Traditional solution methods such as search and sort for optimising complex real life engineering problems can be very expensive in terms of computational time. The considerable execution time tends to inhibit elaborate exploration of the design space and often results to sub-optimal solutions. This paper reports on an engineering optimisation approach designed to bridge the gap between traditi...

A novel genetic algorithm based neural modelling platform is developed for nonlinear dynamic systems. In this platform, the selection of neural inputs, optimisation of the neural network structure and identification of the optimal connection weights are formulated as an integrated optimisation problem. Both one-step-ahead and long-term prediction performances of the neural model are incorporate...

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...

Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method ...

Hyper-heuristics are a class of high-level search methodologies which operate over a search space of heuristics rather than a search space of solutions. Hyper-heuristic research has set out to develop methods which are more general than traditional search and optimisation techniques. In recent years, focus has shifted considerably towards cross-domain heuristic search. The intention is to devel...

Emergency departments (EDs) have been becoming increasingly congested due to the combined impacts of growing demand, access block and increased clinical capability of the EDs. This congestion has known to have adverse impacts on the performance of the healthcare services. Attempts to overcome with this challenge have focussed largely on the demand management and the application of system wide p...

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...