Particle swarm optimization list - smart1004/r_lan GitHub Wiki

2.3. Particle swarm optimization methods Continuous Global Optimization in R - Journal of Statistical Software https://www.jstatsoft.org/article/view/v060i06/v60i06.pdf

Particle swarm optimization is a stochastic, heuristic method introduced by Kennedy and Eberhart (1995). A set (swarm) of candidate solutions (particles) is moved through search space using formulas for position and velocity that depend on the state of the rest of the

pso package pso (Bendtsen 2012) implements a particle swarm optimization algorithm. ppso package ppso (Francke 2012) implements particle swarm optimization along with dynamically dimensioned search algorithms (Tolson and Shoemaker 2007). Options are available for parallelization. hydroPSO package hydroPSO (Zambrano-Bigiarini 2013) implements a particle swarm optimization algorithm; its development was motivated by the need to fit environmental models, though it is a generalpurpose optimizer. NMOF package: PSopt The NMOF package also contains a particle swarm optimization implementation.