Tabu-search simulation optimization approach for flow-shop scheduling with multiple processors - A case study

The flow shop with multiple processors (FSMP) environment is relatively common and has a variety of applications. The majority of academic authors solve the scheduling problem of FSMP using deterministic data that ignore the stochastic nature of a real-world problem. Discrete-event simulation can model a non-linear and stochastic problem and allows examination of the likely behaviour of a proposed manufacturing system under selected conditions. However, it does not provide a method for optimization. The present paper proposes to solve the FSMP scheduling problem by using a tabu-search simulation optimization approach. It features both the stochastically modelling capability of the discrete-event simulation and the efficient local-search algorithm of tabu search. A case study from a multilayer ceramic capacitor manufacturing illustrates the proposed solution methodology. Empirical results show promise for the practical application of the proposed methodologies. Future research opportunities are then addressed.