particle swarm optimization
A population of moving particles, each pulled toward its own best-found point and the swarm's shared best-found point.
In particle swarm optimization, each particle i carries a position x_i and velocity v_i, updated every iteration as v_i \leftarrow w\,v_i + c_1 r_1(p_i-x_i) + c_2 r_2(g-x_i), x_i\leftarrow x_i+v_i, where p_i is the particle's own best-seen position, g is the swarm's shared best-seen position, w is the inertia weight, and r_1,r_2 are fresh random draws each iteration. Unlike a genetic algorithm, particles persist and keep moving rather than being replaced each generation.
Point table
Graph settings
Calculator