APSO 2015 - Special Session on Advances in Particle Swarm Optimization

Particle swarm optimization (PSO), one of the pillars of Swarm Intelligence, is a population-based stochastic optimization technique. Compared with other optimization methods, PSO has no complicated evolutionary operators and adjusts less parameter in the course of training. These merits make it easy to implement, apply, extend and hybridise. Many attempts have been made to improve the performance of the original PSO in past several years. This special session will highlight the latest development in this rapidly growing research area of new PSO and its applications. Authors are invited to submit their original work in the areas including (but not limited to) the following:
Convergence analysis and parameter choice of PSO
Empirical and theoretical analyses of the dynamics of PSO particles and populations
Multiple population cooperative PSO
Advanced bare-bones and distribution-based PSOs
PSOs for stochastic, dynamic, multi-objective and combinatorial optimization problems
Novel combinations of PSO algorithms with other techniques
Novel applications in bioinformatics, image and signal processing, and computational intelligence
Manuscripts should follow LNCS format with at most 12 pages. All accepted papers will be published by Springer-Verlag in the Lecture Notes in Computer Science (LNCS) series or a recommended SCI-indexed journal.