A Novel Fuzzy Logic-Based Improved Cuckoo Search Algorithm

Cuckoo Search (CS) algorithm is a nature-inspired optimization (NIOA) with less control parameters that stable, versatile, and easy to implement. CS has good global search capabilities, but it prone local optima problems. As result, may be possible improve the classic algorithm's capability. Centered on fuzzy set theory, this paper introduces an improved version. The population of solutions been divided into two sets, each solution assigned one sets based its fitness. collection centroids, best advice, Lévy distribution dependent mutation are all used boost population's solutions. With well-accepted objective functions such as Otsu inter class variance Kapur's entropy, experimental analysis conducted CEC-2014 test suite image multi-level thresholding domain. proposed cuckoo (FCS) compared classical CS, PSO, FA, SMA, BA provides satisfactory results.