We present first results of an ontology alignment approach that is based on discrete particle swarm optimisation. In this paper we will firstly describe, how the algorithm approaches the ontology matching task as an optimisation problem, and briefly sketch how the specific technique of particle swarm optimisation is applied. Secondly, we will briefly discuss the results gained for the Benchmark...

Evolutionary Computation niching methods, such as Fitness Sharing and Crowding, are aimed at simultaneously locating and maintaining multiple optima to increase search robustness, typically in multi-modal function optimization. Such methods have been shown to be useful for both single and multiple objective optimisation problems. Niching methods have been adapted in recent years for other optim...

Membrane computing models (also known as P Systems) that solve optimisation problems using genetic algorithms, ant colony optimisation, quantum-inspired evolutionary algorithm and particle swarm optimisation have been defined and are efficiently used in several applications. This paper describes the design of a variant of the existing Distributed P system (dP system) that is augmented with new ...