The customer profile and products have significantly changed in most sectors. The results are high demand variation and diversification, products with shorter life cycles, and increased interest in customized products at reduced prices. One of the bets to keep companies competitive is using reconfigurable manufacturing systems (RMS) due to their reactivity and adaptability by reconfiguring machines and layouts. A big question around this type of system is when and how it should be reconfigured beyond the classic resource allocation and scheduling problems. We propose some exact methods and a genetic algorithm to solve jointly process planning, layout, and scheduling optimization problems in the RMS context.