Most of the man-made technologies are nature-inspired including the popular heuristics or meta-heuristics techniques that have been used to solve complex computational optimization problems. In most of the metaheuristics 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 metaheuristic algorithm, controlling the values of various parameters is one of the most important issues of research. While solving the problem, the parameter value control has a potential to improve the efficiency of the algorithm. The different parameters used in CCA are tuned for better performance of the algorithm and experiment its impact on a set of sample benchmark test functions, then the fine-tuned 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.