In this chapter
- Understanding the inspiration for particle swarm intelligence algorithms
- Understanding and solving optimization problems
- Designing and implementing a particle swarm optimization algorithm
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.
Bird flocks are another ideal example of swarm intelligence in nature. When a single bird is flying, it might attempt several maneuvers and techniques to preserve energy, such as jumping and gliding through the air or using wind currents to carry it in the direction it wants to travel. This behavior indicates some primitive level of intelligence in a single individual.
But birds also need to migrate between seasons. In winter, insects and other types of food are less available, and suitable nesting locations become scarce. Birds tend to flock to warmer areas to take advantage of better weather conditions, improving their likelihood of survival.