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Metal matrix composite (MMC) has established growing usages in the engineering for lightweight high-strength application. However, because of abrasive nature of the reinforcement particles in MMC, machinability is reduced, tool wear is high, yet only diamond tools are appropriate for machining MMC. Being a complex process, it is very complicated to establish optimal parameters for improving cutting performance. Tool flank wear (VBmax) and Average surface roughness (Ra) are the most significant output responses, which decide the machinability of a material. The effect of cutting parameters on output responses of tool flank wear and average surface roughness are conflict with each one another so there is no single optimal mixture of cutting parameters. In this study multi regression model function, based on NSGA-II was used to optimize the machining of Al/20% SiCp MMC using tipped polycrystalline …