Geometric particle swarm optimisation on binary and real spaces: from theory to practice

Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of traditional particle swarm optimization (PSO) that applies naturally to both continuous and combinatorial spaces. In previous work we have developed the theory behind it. The aim of this paper is to demonstrate the applicability of GPSO in practice. We demonstrate this for the cases of Euclidean, Manhattan and Hamming spaces and report extensive experimental results. Categories and Subject Descriptors F.2 [Theory of Computation]: Analysis of Algorithms and Problem Complexity General Terms Theory Keywords Particle Swarm Optimisation, Metric Space, Geometric Crossover

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Cecilia Di Chio, Alberto Moraglio, Riccardo Poli
• Keywords: GECCO 2007, Particle Swarm, Particle Swarm Optimisation, Particle Swarm Optimization