Mitiku, SemuWoldegebriel, Girum2018-07-162023-11-042018-07-162023-11-042012-06http://etd.aau.edu.et/handle/123456789/8680Evolutionary methods are characterized as a set of solution based algorithms to solve multi-objective optimization problems. Evolutionary algorithms have a potential of finding multiple Pareto optimal solution in a single simulation run. In this report we have considered non-dominated sorting genetic algorithm to solve multi objective optimization problem. We have suggested non-dominated sorting genetic algorithm–II for minimization of the objectives. Non-dominated sorting genetic algorithm–II is fast elitist search algorithm which is based on non-domination rank. Non- domination rank provides chance to the population to be chosen to become parent of the next generation. Selection is based on crowded comparison operator to pick population to variation operatorenEvolutionary methods are characterizedAs a set of solution based algorithmsThesis