Seagull-Cuckoo Search Algorithm for Function Optimization
作者
Gyanesh Das,Rutuparna Panda
标识
DOI:10.1109/i2ct51068.2021.9417939
摘要
This paper anticipates to frame a hybrid Seagull Optimization Algorithm - Cuckoo Search (SOA-CS) algorithm for objective function minimization. The migration and attacking strategies of Seagulls are complimented by the social breeding behaviour of cuckoo birds. In addition, the thought of Lévy flight walking methodology is also inherited. Twenty-three standard benchmark test functions are used for validation. To figure out the outcomes - the proposed algorithm converges faster and provides better results over both the SOA and CS algorithms.