Using a standard commercial package, case studies in shape optimisation were used to investigate rules and heuristics for identifying design variables for shape optimisation and incremental updates to the topology of a geometric model from finite element stress results. Topological modifications based on the classical Euler operations were used. The results indicate that intelligent interpretat...

This work presents the optimisation of PIFA (Planar Inverted-F Antenna) antennas in order to achieve a large bandwidth in the 2 GHz band, using an optimisation technique based on genetic algorithms. During the optimisation process, the different antenna models have been evaluated using the finite-difference time domain (FDTD) method. As a result of this optimisation, a simple PIFA antenna was o...

Evolution Strategies are global, direct optimisation algorithms, which have proven their efficiency in engineering applications for a large number of industrial applications. In this paper, the basic algorithm and some of its recent variants for design optimisation are presented. In addition, we give an overview of applications and a comparison to other optimisation algorithms. As an example we...

Previous implementations of the Aq algorithm have used rule optimisation search strategies to attempt to develop optimal classification procedures. These strategies involve generating successive characteristic descriptions each of which is individually of maximal value. This is contrasted with theory optimisation search strategies which, instead, generate successive complete classification proc...

Tidal stream power generation represents a promising source of renewable energy. In order to extract an economically useful amount of power, tens to hundreds of tidal turbines need to be placed within an array. The layout of these turbines can have a significant impact on the power extracted and hence on the viability of the site. Funke et al. [15] formulated the question of the best turbine la...

This paper introduces a modelling concept which aims at creating an environment which allows the application of global optimisation techniques like Genetic Algorithms in dynamic and complex environments. Such environments are often modelled using multi agent systems. The self-evident drawback of multi agent approaches is that global optimisation techniques are not applicable naturally. The mode...

New approaches of particle swarm optimisation algorithm based on Gaussian and Cauchy distributions to adjust the control points of B-spline neural networks are proposed. B-spline networks are trained by gradient-based methods, which may fall into local minimum during the learning procedure. To overcome the problems encountered by the conventional learning methods, particle swarm optimisation  ...

This paper proposes a method for designing EMC shielding enclosures using a peer-to-peer based distributed optimisation system based on a modified particle swarm optimisation (PSO) algorithm. This optimisation system is used to efficiently obtain optimal solutions to a shielding enclosure design problem by sampling only a small fraction of the total problem space. Such a system would find use i...

This paper considers a residential market with real-time electricity pricing and flexible electricity consumption profiles for customers. Such a market raises an optimisation problem for home automation systems where they need to schedule consumption activities to reduce costs, whilst maintaining a base level of comfort and convenience. This optimisation problem faces uncertainty in real-time p...

Evolutionary algorithms are well established methods for shape and design optimisations and they are applied to a large variety of problems. Especially for the optimisation of aerodynamic properties various publications demonstrate the potential of the method. Two major problems in the application of evolutionary optimisation methods for the improvement of aerodynamic properties are the represe...