The main motive of the modern manufacturing industry is high productivity, precise dimensional accuracy and superior surface finish. It is very difficult and time-consuming to get the ideal combination of machining variables when the objectives are conflicting in nature. The advent of algorithm-based optimization techniques is very beneficial to solve complex and lengthy mathematical problems. In this paper, a hybrid concept of multi-criteria decision-making has been proposed with the help of a multi-objective genetic algorithm (GA) and combined compromise solution (CoCoSo) for the central composite design of the experiment. The input variables have been selected as pulse-on time, pulse-off time, peak current and voltage for the machining of Ni-based hardfaced deposit. Peak current has been observed as the most influential parameter, followed by pulse on time for material removal rate and surface roughness. The increase in peak current reduces the machined surface quality by 31.84% since the tendency of micro cracks and cavities formation increases under the influence of intense discrete discharge energy. The Pareto curves exhibited contradicting influences during wire electric discharge machining of the Ni-based hardfaced deposit and provided a collection of optimal non-dominant possibilities. GA-CoCoSo hybrid approach has provided the ideal machining condition at the combination of 61 A current, 18 μs Ton, 34 μs Toff and 30 V SV with a marginal error of 4.01% and 3.27% for material removal rate and surface roughness, respectively. The suggested hybrid optimization yielded a maximum material removal rate of 14.583 mm2/min and a minimum surface roughness of 2.019 µm.