Bi-objective optimization of integrating configuration generation and scheduling for reconfigurable flow lines using NSGA-II

Reconfigurable manufacturing system (RMS) is a new manufacturing system paradigm suited to the era of mass customization. A RMS is able to change its configuration by physical reconfiguration and/or logical reconfiguration, to provide exact functionality and capacity needed for every demand period. For the reconfigurable flow line (RFL) in which multiple parts within the same part family can be produced simultaneously, optimal design of physical configuration (called configuration generation) and proper scheduling of multiple products are crucial to operate RFL in a cost-effective manner. Considering the close coupling between configuration generation and scheduling of multiple products for RFL, a new multi-objective mixed integer programming model is established for the integrated optimization of configuration generation and scheduling. The two conflicting objectives are to minimize total cost including capital cost and reconfiguration cost and to minimize total tardiness. The validity of the model is verified through case analysis implemented by LINGO software. Subsequently, the nondominated sorting genetic algorithm II (NSGA-II) is adopted to obtain a set of nondominated solutions. In the NSGA-II, a hybrid encoding method ensuring any chromosome a feasible solution is devised. Case study is utilized to illustrate the effectiveness of the NSGA-II for solving the problem. The case study also reveals that only if performing configuration generation and scheduling concurrently can a set of solutions balancing cost and tardiness be identified effectively for the RFL.