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A method is presented for function optimisation that generalises the Simulated Annealing algorithm by applying convolutions of the target function with smooth, infinitely differentiable kernels. Hence the search for a gl...

Subjects / keywords: Computer science; Image registration; Affine transformation; Artificial intelligence; Similarity (geometry); Modal; Component (thermodynamics); Data mining; Computer vision; Image (mathematics); Mathematics; Physics

Evolutionary Computation (EC) have been applied to a great number of optimisation problems with some success, specially in fields such as production operations in manufacturing industry, parallel and distributed systems,...

This paper presents an Ant Colony Optimisation (ACO) model for the Multiple Knapsack Problem (MKP). The ACO algorithms, as well as other evolutionary metaphors, are being applied successfully to diverse heavily constrain...

This paper presents an Ant Colony (AC) model for the Multiple Knapsack Problem (MKP). The ant colony metaphor, as well as other evolutionary metaphors, was applied successfully to diverse heavily constrained problems. An...

Evolutionary algorithms (EAs) can be used as optimisation mechanisms. Based on the model of natural evolution, they work on populations of individuals instead of on single solutions. In this way, the search is performed ...

In this thesis, a novel approach to automatically install threaded inserts into additive manufactured parts is developed and validated. Such an approach is highly relevant in the context of process automation and product...

In this paper a thermodynamic approach is presented to the problem of convergence of evolutionary algorithms. The case of the Simulated Annealing algorithm for optimisation is considered as a simple evolution strategy wi...

The Rijndael cipher, designed by Joan Daemen and Vincent Rijmen and recently selected as the official Advanced Encryption Standard (AES) is well suited for hardware use. This implementation can be carried out through sev...

In this paper a thermodynamic approach is presented to the problem of convergence of evolutionary algorithms. The case of the Simulated Annealing algorithm for optimisation is considered as a simple evolution strategy wi...

Sequential and parallel evolutionary algorithms (EAs) are developed and evaluated on two hard optimisation problems arising in the field of Telecommunications: designing error correcting codes, and finding optimal placem...

The aim of the present research was to study the optimisation of mevastatin production by Penicillium citrinum MTCC 1256. Optimization of fermentation medium was carried out by response surface methodology. Simultaneous ...

This work summarizes results when facing the problem of allocating a number of nonidentical tasks in a parallel system. The model assumes that the system consists of a number of identical processors and that only one tas...

The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g....

Given a combinatorial optimisation problem, there are typically multiple ways of modelling it for presentation to an automated solver. Choosing the right combination of model and target solver can have a significant impa...

Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most ...

The main goal of this thesis was to design new parallel processing strategies specially conceived for distributed environments in order to solve numerical and structural problems from the field of process systems enginee...

Contrasting with conventional approaches to crossover, Multiple Crossover Per Couple (MCPC) is an alternative, recently proposed [1], approach under which more than one crossover operation for each mating pair is allowed...

As a new promising crossover method, multiple crossovers per couple (MCPC) deserves special attention in evolutionary computing field. Allowing multiple crossovers per couple on a selected pair of parents provided an ext...