This work is aimed at optimizing the various parameters of the electro discharge machining process in order to Maximize material removal rate (MRR) and Minimize electrode wear rate (EWR) for machining silicon or resin bonded silicon carbide, which is widely used in various applications like high-temperature gas turbines, bearings, seals and linings of industrial furnaces. The five parameters being optimized are intensity supplied by the generator of the EDM machine, open voltage, pulse on time, duty cycle and pressure of flushing fluid. The polynomial models for MRR and EWR proposed by Luis, Puertas and Villa  in terms of the five input parameters was used for formation of the objective function. Optimization was carried out using the multi objective genetic algorithm, which is a heuristic search technique that mimics natural selection. A Pareto-optimal front was obtained using this technique, and the points lying on this front represent the set of optimal solutions for the optimization problem. The resultant Pareto– optimal front can be used to select the appropriate operating conditions depending on the specific MRR, EWR or combination requirements.