Production scheduling for reconfigurable assembly systems: Mathematical modeling and algorithms

This study generalizes the scheduling problem of a reconfigurable assembly system where the configuration of the system is changeable. There are different job sets and each has a unique fittest configuration, although the job set can be still operated in a less fit configuration. Therefore, besides the classical scheduling decision, the problem decides whether to move to the configuration that most suits a job set or continue the standing configuration. The available models cannot address this specification. In this study, we first explicitly define different aspects of the problem and then develop a mathematical formulation to formally model the problem. We solve the small-sized instances with up to 6 jobs using the model and commercial software of operations research. To effectively solve large instances of the problem, we also propose two different artificial immune algorithms. In this regard, we develop an encoding scheme as well as two hypermutations and a local search that match the encoding scheme. Using numerical experiments, both the model and the performance of the proposed algorithm are being evaluated.