Cuckoo Search (CS) Algorithm
Erik Cuevas, Alma María Gómez Rodríguez · 2020
In this chapter, the main characteristics of the Cuckoo Search (CS) scheme are discussed. Due to its importance, a multimodal version of the CS method is also reviewed. CS is a simple and effective global optimization algorithm that is inspired by the breeding behavior of some cuckoo species. One of the most powerful features of CS is the use of Lévy flights to generate new candidate solutions. Under this approach, candidate solutions are modified by employing many small changes and occasionally large jumps. As a result, CS can substantially improve the relationship between exploration and exploitation, still enhancing its search capabilities. Despite such characteristics, the CS method still fails in providing multiple solutions in a single execution. In order to overcome such inconvenience, a multimodal optimization algorithm called the multimodal CS (MCS) is also presented. Under MCS, the original CS is enhanced with multimodal capacities by means of (1) the incorporation of a memory mechanism to efficiently register potential local optima according to their fitness value and the distance to other potential solutions, (2) the modification of the original CS individual selection strategy to accelerate the detection process of new local minima, and (3) the inclusion of a depuration procedure to cyclically eliminate duplicated memory elements.