Abstract:

Aiming at the disadvantages of the basic cuckoo search(CS) algorithm such as weaker local search ability,slower convergence rate and poorer optimization precision,this paper studies the quantum inspired cuckoo search algorithm.Firstly,we enabled the cuckoos with heterogeneous search behaviors towards the nests with the help of quantum mechanism.Then three measures which can improve the cuckoos local search capability were introduced on this basis,namely the introduction of a similar inertia weight to the equation of renewal of the nests positions,an adaptively decreased probability of the cuckoo nests being replaced with a randomly generated new one,and the improvement of increment with a random disturbance.A graphical comparison of the original CS algorithm and the quantum one used for optimization of two kinds of benchmark functions shows that the latter algorithm possesses greater advantages over the original one with a better precision.

Key words: cuckoo search algorithm;quantum mechanism;benchmark functions;local search