Computation reduction for a large scale Markov process model to analyse multistage production systems

In order to solve a large-scale Markov decision process which optimizes the control strategy of a multistaged production/inventory system, a computation reduction and memory management system was used. A ‘nuclear’ state space of relatively small size was found to substitute for the original state space. A circular comparison technique and a location index storage method were used to save computer memory used for storing the model.