Geometric Particle Swarm Optimization. (16th December 2007)

• Record Type: Journal Article
• Authors: Moraglio, Alberto; Di Chio, Cecilia; Togelius, Julian; Poli, Riccardo
• Other Names: Blackwell T. Academic Editor.
• Is Part Of: Journal of artificial evolution and applications. Volume 2008(2008)
• Publication Date: 2007-12-16
• Subjects: Evolutionary programming (Computer science) -- Periodicals; Evolutionary programming (Computer science); Periodicals; Electronic journals; 006.3823
• DOI: 10.1155/2008/143624
• Languages: English
• ISSNs: 1687-6229

Abstract

Abstract : Using a geometric framework for the interpretation of crossover of recent introduction, we show an intimate connection between particle swarm optimisation (PSO) and evolutionary algorithms. This connection enables us to generalise PSO to virtually any solution representation in a natural and straightforward way. The new Geometric PSO (GPSO) applies naturally to both continuous and combinatorial spaces. We demonstrate this for the cases of Euclidean, Manhattan and Hamming spaces and report extensive experimental results. We also demonstrate the applicability of GPSO to more challenging combinatorial spaces. The Sudoku puzzle is a perfect candidate to test new algorithmic ideas because it is entertaining and instructive as well as being a nontrivial constrained combinatorial problem. We apply GPSO to solve the Sudoku puzzle.