Swarm and Evolutionary Computation To tackle complex real world
problems, scientists have been looking into natural processes
and creatures - both as model and metaphor - for years.
Optimization is at the heart of many natural processes including
Darwinian evolution, social group behavior and foraging
strategies. Over the last few decades, there has been remarkable
growth in the field of nature-inspired search and optimization
algorithms. Currently these techniques are applied to a variety
of problems, ranging from scientific research to industry and
commerce. The two main families of algorithms that primarily
constitute this field today are the evolutionary computing
methods and the swarm intelligence algorithms. Although both
families of algorithms are generally dedicated towards solving
search and optimization problems, they are certainly not
equivalent, and each has its own distinguishing features.
Reinforcing each other's performance makes powerful hybrid
algorithms capable of solving many intractable se