A hybrid multi-objective optimization method combining second-order polynomial regression, NSGA-II and TOPSIS is deployed here for attaining optimal solutions which balances the trading-off between hole quality metrics and MRR. First, in Section 3, second-order polynomial regression model is used to find the mapping between response variables (thrust force, hole wall temperature and delamination factor Fda) and machining parameters (feed rate 𝐹𝐹 𝑓𝑓 and spindle speed 𝑆𝑆). Then, the optimal non-dominated solutions (Pareto solutions) can be obtained through NSGA-II algorithm in Section 4. Finally, the TOPSIS method is deployed to rank the multiple Pareto solutions according to their proximity to the ideal solution, hence identifying the top ranking solutions, in Section 5. The flow-chart in Fig. shows the multi-objective optimization procedure in this study.