All optimisation algorithms have parameters that affect their performance and reliability. Usually the default values of these parameters are problem-dependent. Regardless of this fact it is common practice to use some default values that are provided with the optimisation algorithm. Finding the optimal values of these parameters is a computationally expensive optimisation problem also known as...

Design optimisation of electrical machines, in particular permanent magnet synchronous disc motors, is very important, but quite a complicated problem. A reasonably simplified form of the design procedure may be attacked by various approaches accumulated into two main topics; classical optimisation techniques (deterministic methods) or genetic algorithms (stochastic methods). Genetic algorithm ...

The paper proposes a design procedure for the creation of a robust and effective hybrid algorithm, tailored to and capable of carrying out a given design optimisation task. In the course of algorithm creation, a small set of simple optimisation methods is chosen, out of which those performing best will constitute the hybrid algorithm. The simplicity of the method allows implementing ad-hoc modi...

Our aim is to realise an agent-based Grid simulator for studying "Grid Query Optimisation Strategies", as partially described in [SSS+01]. The purposes of this document are the following: • To identify some HEP use cases and, based on these use cases and requirements, to identify some user-level and Grid-level query optimisation opportunities. • To define an architecture for the simulator, in w...

The basic feature of the optimisation-based clearance approach is to reformulate the clearance problems as equivalent minimum distance problems for which ”anti”-optimisation is performed to determine the worst-case parameter combination/flight condition leading to worst performance. The basic requirements for the applicability of the optimisation-based approach are the availability of suitable ...

Multi-objective optimisation is regarded as one of the most promising ways for dealing with constrained optimisation problems in evolutionary optimisation. This paper presents a theoretical investigation of a multi-objective optimisation evolutionary algorithm for solving the 0-1 knapsack problem. Two initialisation methods are considered in the algorithm: local search initialisation and greedy...

In this paper we focus on randomised evolutionary optimisation. We introduce a general framework for the optimisation of data models, based on the concept of evolution. This evolution is guided by a randomised schema mutator. Although our approach is expressed in terms of database optimisation, our ideas are applicable to other elds of randomised evolutionary optimisation of computer models, es...

In this paper, we present the famous temporal partitioning algorithms that temporally partition a data flow graph on reconfigurable systems. We have classified these algorithms into four classes: 1) whole latency optimisation algorithms; 2) whole communication cost optimisation algorithms; 3) whole area optimisation algorithms; 4) whole latency-communication cost optimisation algorithms. These ...

Online set-point optimisation which cooperates with model predictive control (MPC) and its application to a yeast fermentation process are described. A computationally efficient multilayer control system structure with adaptive steady-state target optimisation (ASSTO) and a suboptimal MPC algorithm are presented in which two neural models of the process are used. For set-point optimisation, a s...