Design of Optimal CMOS Inverter for Symmetric Switching Characteristics Using Firefly Algorithm with Wavelet Mutation

In this article, a population based meta-heuristic search method called Firefly Algorithm with Wavelet Mutation (FAWM) is applied for the optimal switching characterization of CMOS inverter. In Firefly Algorithm (FA), behaviour of flashing firefly towards its competent mate is structured. In this algorithm attractiveness depends on brightness of light and brighter fireflies are considered as more attractive among the population. For the present minimization based optimization problem, brightness varies inversely proportional to the error fitness value, so the position of the brightest firefly gives the optimum result corresponding to the least error fitness in multidimensional search space. FAWM incorporates a new definition of swarm updating with the help of wavelet mutation based on wavelet theory. Wavelet mutation enhances the FA to explore the solution space more effectively compared with the other optimization methods. The performance of FAWM is compared with real coded genetic algorithm (RGA), and conventional PSO reported in the literature. FAWM based design results are also compared with the PSPICE results. The comparative simulation results establish the FAWM as a more competent optimization algorithm to other aforementioned evolutionary algorithms for the examples considered and can be efficiently used for CMOS inverter design.