A suboptimal class of decentralized hedging production policies in single part-type, stochastic M-machine flow shop

Production optimization is considered for stochastic single-part M-machine flow shops over the class of so-called decentralized hedging production policies. A decomposition methodology previously developed for tandem two-machine systems is generalized to M-machine flow shops. Using a machines decoupling approximation and a so-called demand averaging principle, the considered M-machine flow shop is decomposed into a set of M decoupled single machine systems with known analytical production costs. The overall production cost obtained by adding individual costs is parametrized by M critical levels of parts to be determined. Subsequently, the best decentralized hedging production policy is found by minimizing the overall analytical cost over the hedging levels space. The predicted performance of the proposed class of decentralized policies is tested and validated on a number of three-machine flow shops with the help of Monte Carlo simulation techniques