ABSTRACT
Stochastic Diffusion Search (SDS) belongs to the extended family of swarm intelligence algorithms. It was first introduced in 1989 and is the first Swarm Intelligence metaheuristic. In contrast to many nature-inspired algorithms, SDS has a strong mathematical framework describing its behaviour and convergence. The algorithm has been applied to both discrete and continuous problems and is equipped with mechanisms which makes it suitable for decomposable problems, where components of the fitness functions are evaluated independently. This chapter provides the details of standard SDS, thus allowing researchers to apply the algorithm to various problems.
