Improved Cuckoo Search Algorithm with Novel Searching Mechanism for Solving Unconstrained Function Optimization Problem

摘要

Cuckoo search (CS) algorithm is a new biological heuristic algorithm and simulates the cuckoo's seeking nest and spawning behavior and introduces levy flight mechanism. In order to improve the convergence velocity and optimization accuracy of cuckoo search algorithm, by combining the learning-evolving thought with Gaussian distribution, a new searching mechanism that with a learning-evolving searching guider is proposed. Then combining the new searching mechanism proposed with the Levy Flight searching mechanism according to a selection probability, a new searching mechanism cuckoo search (MCS) algorithm is formed. The result of functions testing under different dimensions proves the superiority of new proposed MCS algorithm.