In recent years the area of Evolutionary Computation has come into its own. Two of the popular developed approaches are Genetic Algorithms and Particle Swarm Optimisation, both of which are used in optimisation problems. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare th...

Particle swarm methods are inspired from the dynamics of social interaction and employ information sharing to seek solutions to difficult optimisation problems. In this paper we introduce an approach that combines ideas from particle swarm optimisation (PSO) and the theory of nonextensive statistical mechanics. We develop two algorithms that adopt this approach and conduct an experimental study...

In this paper, we address full-body articulated human motion tracking from multi-view video sequences acquired in a studio environment. The tracking is formulated as a multi-dimensional nonlinear optimisation and solved using particle swarm optimisation (PSO), a swarm-intelligence algorithm which has gained popularity in recent years due to its ability to solve difficult nonlinear optimisation ...

Intrusion detection is a mechanism used to protect a system and analyse and predict the behaviours of system users. An ideal intrusion detection system is hard to achieve due to nonlinearity, and irrelevant or redundant features. This study introduces a new anomaly-based intrusion detection model. The suggested model is based on particle swarm optimisation and nonlinear, multi-class and multi-k...

This paper presents and discusses the results produced by the MapPSO system for the 2010 Ontology Alignment Evaluation Initiative (OAEI). MapPSO is an ontology alignment approach based on discrete particle swarm optimisation (DPSO). Firstly, specific characteristics of the MapPSO system and their relation to the results obtained in the OAEI are discussed. Secondly, the results for the benchmark...

This paper proposes a multi-objective optimisation model and particle swarm optimisation solution method for the robust dynamic scheduling of permutation flow shop in the presence of uncertainties. The proposed optimisation model for robust scheduling considers utility, stability and robustness measures to generate robust schedules that minimise the effect of different real-time events on the p...

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...

Currently, two very similar versions of PSO are available that could be called “standard”. While it is easy to merge them, their common drawbacks still remain. Therefore, in this paper, the author goes beyond simple merging by suggesting simple yet robust changes and solving a few well-known, common problems, while retaining the classical structure. The results can be proposed to the “swarmer c...