Hydrocracking is a petroleum refining process where cracking occurs simultaneously with hydrogenation to convert heavy petroleum feedstocks into desired lighter products. In this study, multi-objective optimization of an industrial hydrocracking unit has been performed for the first time, to find scope for further improvements and to provide a range of optimal solutions. The reactor model was simulated based on a discrete lumped model approach to kinetic modeling. The kinetic and product distribution parameters were fine-tuned using available industrial data. The real-coded elitist nondominated sorting genetic algorithm was used to carry out the multi-objective optimization study. The Pareto-optimal solutions for the hydrocracker unit are presented, and their significant features are discussed.