Reconfigurable Manufacturing Systems (RMS) emerged from companies’ needs to increase their responsiveness to an uncertain market, in which customers are increasingly demanding mass-customised products. Companies focused on mass customisation mainly use the modular product design (MPD) strategy to cost-effectively provide a large product variety. Hence, coupling the MPD with the manufacturing in RMS seems to be a good strategy to effectively provide mass-customised products with lower costs. However, few papers have concurrently optimised the modular products’ and RMS’s configurations for that end. Further, very few papers have explored the RMS’s layout configuration. In order to fill these gaps, this paper proposes a Nonlinear Integer Programming model that integrates the configuration of modular products and RMS, driven by individual customer requirements, to minimise manufacturing costs of mass-customised products. An approach combining a Modified Brute-Force Algorithm (MBFA) and a genetic algorithm (GA) is proposed and compared with a CPLEX-based approach for a small-sized problem, proving its ability to find an optimal solution in lower computation time. An illustrative example of modular smartphones confirms the MBFA-GA’s ability to solve medium/large-sized problems in a reasonable amount of time while ensuring an optimal product configuration that meets customer requirements.