An improved cuckoo search algorithm based on DV-Hop for location in WSN

In this paper, an improved cuckoo search algorithm with fuzzy logic and Gauss–Cauchy strategy (ICS-FG) is proposed, that integrates the meta-heuristic algorithm with the traditional method. To regulate the dynamic adjustment of parameters, we proposes a fuzzy logic based on population diversity. The Gauss–Cauchy strategy improve the algorithm’s search accuracy while enhancing its robustness. Experimental results obtained from well-known benchmark functions demonstrate the advance of the ICS-FG approach over the parallel compact cuckoo search algorithm (pcCS), improved adaptive genetic algorithm (IAGA). The proposed ICS-FG approach achieves a lower positioning error than pcCS, IAGA, and other state-of-the-art algorithms.