Control of M/Cox-2/s make-to-stock systems

This study considers a make-to-stock production system with multiple identical parallel servers, fixed production start-up costs and lost sales. Processing times are assumed to be two-phase Coxian random variables that allows us to model the systems having rework or remanufacturing operations. First, the dynamic programming formulation is developed and the structure of the optimal production policy is characterized. Due to the highly dynamic nature of the optimal policy, as a second contribution we propose an easy-to-apply production policy. The proposed policy makes use of the dynamic state information and controlled by only two parameters. We test the performance of the proposed policy at several instances and reveal that it is near optimal. We also assess the value of dynamic state information in general by comparing the proposed policy with the well-known static inventory position based policy.