Analysis of Algorithms

Many optimization algorithms have been developed by drawing inspiration from swarm intelligence (SI). These SI-based algorithms can have some advantages over traditional algorithms. In this chapter, we carry out a critical analysis of these SI-based algorithms and other nature-inspired algorithms by analyzing the ways they mimic evolutionary operators. We also analyze ways of achieving exploration and exploitation in algorithms by using mutation, crossover, and selection. In addition, we study these algorithms using dynamic systems, self-organization, and the Markov chain framework. Finally, we provide some discussion and topics for further research.