In small workshops, a more number of holes on aero engine parts are drilled successively in one process to confirm positional accuracy. Because of the fast time-varying drill wear, the surface roughness of the holes is unstable and difficult to be satisfied. To the present end, this paper presents a varying-parameter drilling (VPD) method to enhance machining efficiency and hole surface roughness for multi-hole parts manufactured from Al 7075 alloys. This method uses varying cutting parameters for every hole to adapt to the varying drill wear. The major problem of this method deceit in an optimization issue during which the optimal combination of setting of cutting parameters have to be found, with the target of the interval and also the constaint of the opening surface roughness, because sequence of cutting parameter encompasses a important aspect and therefore the surface roughness of all the holes must be guaranteed, the challenge of this optimization issue is that the strict constraint with a sophisticated non-linear boundary of the feasible zone. To cope with the convergence complexity of the searching algorithm, a metaheuristic method supported particle swarm optimization (PSO) algorithm with a self-adaptive penalty method (SAPM) is applied. The drilled hole surface roughness is predicted with a radial basis function (RBF) neural network. The various types of drill wear comprising flank wear, crater wear, chisel wear and outer corner wear are considered and the grey relational analysis (GRA) is deployed to pick the input drill wear parameters to the network. The PSO algorithms integrate with the SAPM is used to search the overall optimal solution of the optimization problem. It is found that the satisfied solutions can be searched in all the trials with the proposed metaheuristic algorithms, even though the proportion of feasible solutions is severely fluctuant during the searching process. The drilling experiment confirm that, when compared with the fixed-parameter drilling, the proposed VPD and the metaheuristic algorithm method for solving the optimization problem can effectively improve machining efficiency and surface quality for drilling Al 7075 alloy multi-hole parts.