Particle Swarm Optimization
Few words about PSO:
In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. Each particle keeps track of its coordinates in the problem space which are associated with the best solution (fitness) it has achieved so far. The fitness value called pbest is then stored. Another value that is tracked by the particle swarm optimizer is the best value, obtained so far by any particle in the neighbors of the particle. This location is called lbest. When a particle takes all the population as its topological neighbors, the best value is a global best, called gbest.
The particle swarm optimization concept consists of updating the velocity of accelerating each particle toward its pbest and lbest locations at each time step. Acceleration is weighted by a random term, with separate random numbers being generated for acceleration toward pbest and lbest locations. Imagine now that each PSO particle can also change its dimension, which means that they have the ability to jump to another (solution space) dimension as they see fit. In that dimension they simply do regular PSO moves but in any iteration they can still jump to any other dimension.
In upcoming post we will share some good article related to PSO stay tuned.
In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. Each particle keeps track of its coordinates in the problem space which are associated with the best solution (fitness) it has achieved so far. The fitness value called pbest is then stored. Another value that is tracked by the particle swarm optimizer is the best value, obtained so far by any particle in the neighbors of the particle. This location is called lbest. When a particle takes all the population as its topological neighbors, the best value is a global best, called gbest.
The particle swarm optimization concept consists of updating the velocity of accelerating each particle toward its pbest and lbest locations at each time step. Acceleration is weighted by a random term, with separate random numbers being generated for acceleration toward pbest and lbest locations. Imagine now that each PSO particle can also change its dimension, which means that they have the ability to jump to another (solution space) dimension as they see fit. In that dimension they simply do regular PSO moves but in any iteration they can still jump to any other dimension.
In upcoming post we will share some good article related to PSO stay tuned.
No comments:
Post a Comment