Geometric PSO + GP = Particle Swarm Programming



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 this paper we
apply GPSO to the space of genetic programs represented as
expression trees, uniting the paradigms of genetic programming
and particle swarm optimization. The result is a particle swarm
flying through the space of genetic programs. We present initial
experimental results for our new algorithm.


IEEE Congress on Evolutionary Computation, January 2008

Cited by

Year 2010 : 3 citations

 Sergio Consoli, José Andrés Moreno-Pérez, Kenneth Darby-Dowman, Nenad Mladenovi? (2010).Discrete Particle Swarm Optimization for the minimum labelling Steiner tree problem. Journal of Natural Computing, Vol 9, Number 1, pp. 29-46, Springer, 2010.

 Mohammed El-Abda, Hassan Hassanb, Mohab Anisa, Mohamed S. Kamela and Mohamed Elmasrya (2010). Discrete cooperative particle swarm optimization for FPGA placement. Applied Soft Computing, Volume 10, Issue 1, January 2010, pp. 284-295, Elsevier.

 S Narmadha, V Selladurai, G Sathish (2010). Efficient Inventory Optimization of Multi Product, Multiple Suppliers with Lead Time using PSO, Arxiv preprint arXiv:1002.2196, 2010.