Impact of Parameter Tuning on the Cricket Chirping Algorithm

Most of the man-made technologies are nature-inspired including the popular heuristics or metaheuristics techniques that have been used to solve complex computational optimization problems. In most of the meta-heuristics algorithms, adjusting the parameters has important significance to obtain the best performance of the algorithm. Cricket Chirping Algorithm (CCA) is a nature inspired meta-heuristic algorithm that has been designed by mimicking the chirping behavior of the cricket (insect) for solving optimization problems. CCA employs a set of parameters for its smooth functioning. In a meta-heuristic algorithm, controlling the values of various parameters is one of the most important issues of research. While solving the problem, the parameter values have a potential to improve the efficiency of the algorithm. The different parameters used in CCA are tuned for better performance of the algorithm through experiments conducted on a set of sample benchmark test functions and then, the finetuned CCA is compared with some other meta-heuristic algorithms. The results show the optimal choice of the various parameters to solve optimization problems using CCA.