A new hybrid CS-GSA algorithm for function optimization

This paper presents a new hybridized population-based Cuckoo search-Gravitational search algorithm (CS-GSA) for function minimization. The main thrust is to supplement the exploration capability (of the search space) of the Gravitational search algorithm in the Cuckoo search, which is popular for its exploitation behavior. The other idea is to get a faster solution. Standard test functions are used to compare the performance (best solution) of the proposed algorithm with both CS and GSA algorithms. The results show that the proposed algorithm converge with less number of function evaluations than both CS and GSA algorithms.