The multi-objective optimization approach has a large influence in the industrial production scheduling. The goal of such optimization is to find a production schedule that satisfies different, usually contradictory, production and business constraints. In the paper, memetic versions of three multi-objective algorithms with different approaches to problem solving are implemented. The customized reproduction operators and local search procedures are also used. These memetic algorithms are applied to real order-lists from a production company. It is shown that the multi-objective approaches are able to find high-quality solutions, also when quick respond is required to adapt to dynamic business conditions. According to the results it is concluded that for the two tested real-world problems the IBEA confirmed its superiority over the NSGA-II and SPEA2.