Master Production Schedule (MPS) plays an important role in the specifications of optimization levels of resources for production. MPS describes what is to be produced and also refers to the time in which the production is scheduled to be completed. The creation of MPS becomes complex when objectives like maximization of service level, resource utilization and minimization of inventory levels, overtime, chance of occurring stock outs, setup times etc. are considered. Such multi objective parameter optimization problems can effectively be solved using the nature inspired population based algorithms. Differential Evolution (DE) is one such most powerful parameter optimization algorithm, which doesn’t require many control parameters. This work proposes a new Multi-objective Optimization for MPS using Differential Evolution (MOOMDE). The MOOMDE is applied to a benchmark problem and the results demonstrate that the use of DE yields the most optimal solution for MPS problems.