chapter seven

7 Swarm intelligence: Particles

 

This chapter covers

  • Understanding the inspiration for particle swarm intelligence algorithms
  • Understanding and solving optimization problems
  • Designing and implementing a particle swarm optimization algorithm

7.1 What is particle swarm optimization?

Particle swarm optimization (PSO) is another swarm algorithm. Swarm intelligence relies on emergent behavior of many individuals to solve difficult problems as a collective. We saw in Chapter 6 how ants can find the shortest paths between destinations through their use of pheromones.

7.2 Optimization problems: A slightly more technical perspective

7.3 Problems applicable to particle swarm optimization

7.4 Representing state: What do particles look like?

7.5 Particle swarm optimization life cycle

7.5.1 Initialize the population of particles

7.5.2 Calculate the fitness of each particle

7.5.3 Update the position of each particle

7.5.4 Determine the stopping criteria

7.6 Use cases for particle swarm optimization algorithms

7.7 Summary of particle swarm optimization