ABSTRACT
In present research, novel bat algorithm (NBA) and bird swarm algorithm (BSA), two novel bio-inspired metaheuristic algorithms, are employed to investigate the laser micro-drilling process as well as to find the optimal process parameters to improve the product quality. The novel bat algorithm is inspired by habitat selection behaviours of bats and their self-adaptive compensation for the Doppler effect in echoes. The bird swarm algorithm is inspired by the social behaviours and social interactions in bird swarms. The response surface method (RSM) is used to establish the empirical equations to correlate the laser micro-drilling input parameters with drilled hole quality characteristics. The developed equations are further used as objective functions for determination of optimal parameters setting using NBA and BSA. Both algorithms are compared for their accuracy, repeatability, convergence rate and computational time. The results derived from these algorithms are used for plotting parametric trends to analyze the effects of different control parameters on product quality.
