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Wire electric discharge machining is one of the fastest growing machining processes. In view of the complexity of the process, controlling the machining parameters without compromising on the response parameters is a tedious process. In this paper, a new optimization strategy, by coupling grey relational analysis (GRA) with genetic algorithm (GA), is proposed to simultaneously optimize the response parameters. Experiments were conducted on EN 353 work material to study the effects of various process parameters on the response parameter such as material removal rate (MRR), surface roughness (SR), and cutting width (kerf). Process parameters such as pulse on time, pulse off time, peak current, and servo voltage are considered. ANOVA analysis was carried out to find the parameters affecting the responses with the help of 3D surface plots. A regression model is formed for each response and this model serves as the objective function for GA. In the proposed GRA coupled with GA method, GA is main technique and GRA entropy is used to generate weights systematically. Search is made for optimal solution in a global space. Hence, the obtained solution is not within the conducted experiments alone, it is a global optimal solution in the selected range of process parameter. Pareto surface and contour plots also plotted to help selection of responses based on individual priorities.