Using a geometric framework for the interpretation of crossover of recent introduction, we show an intimate connection between particle swarm optimization (PSO) and evolutionary algorithms. This connection enables us to generalize PSO to virtually any solution representation in a natural and straightforward way. We demonstrate this for the cases of Euclidean, Manhattan and Hamming spaces.

Since 2006, three successive standard PSO versions have been put on line on the Particle Swarm Central [10], namely SPSO 2006, 2007, and 2011. The basic principles of all three versions can be informally described the same way, and in general, this statement holds for almost all PSO variants. However, the exact formulae are slightly di erent, because they took advantage of latest theoretical an...

Article history: Received: 14.5.2015. Received in revised form: 28.11.2015. Accepted: 1.12.2015. Tool travel and tool switch scheduling are two major issues in hole-making operations. It is necessary to find the optimal sequence of operations to reduce the total processing cost of hole-making operations. In this work therefore, an attempt is made to use both a recently developed particle swarm ...

This paper develops a hybrid Constrained Genetic Algorithm and Particle Swarm Optimisation method for the evaluation of the load flow in heavy-loaded power systems. The new algorithm is demonstrated by its applications to find the maximum loading points of three IEEE test systems. The paper also reports the experimental determination of the best values of the parameters for use in the Particle ...

An efficient oscillating inertia weight of particle swarm optimisation for tracking optima in dynamic environments Javidan Kazemi Kordestani, Alireza Rezvanian & Mohammad Reza Meybodi To cite this article: Javidan Kazemi Kordestani, Alireza Rezvanian & Mohammad Reza Meybodi (2016) An efficient oscillating inertia weight of particle swarm optimisation for tracking optima in dynamic environments,...

This paper develops a hybrid Constrained Genetic Algorithm and Particle Swarm Optimisation method for the evaluation of the load flow in heavy-loaded power systems. The new algorithm is demonstrated by its applications to find the maximum loading points of three IEEE test systems. The paper also reports the experimental determination of the best values of the parameters for use in the Particle ...

Particle swarm optimisation (PSO) is a biologically-inspired, population-based optimisation technique that has been successfully applied to various problems in science and engineering. In the context of semantic technologies, optimisation problems also occur but have rarely been considered as such. This work addresses the problem of ontology alignment, which is the identification of overlaps in...

Compositions measurement is a vitally critical issue for the modelling and control of distillation process. The product compositions of distillation columns are traditionally measured using indirect techniques via inferring tray compositions from its temperature or by using an online analyser. These techniques were reported as inefficient and relatively slow methods. In this paper, an alternati...

The purpose of this paper is to demonstrate the application of particle swarm optimisation to the detection of simple objects. The paper’s new contribution to object detection is application of particle swarm optimisation for extraction of geometric properties of an object in an image for accurate recognition especially in noisy environments. In this approach, the edges and the corners of an ob...