Parallel algorithm for setting work-in-process levels for multi-product CONWIP systems

Reducing work-in-process (WIP) inventory is continuing to be an important business need because of several factors including the need to reduce working capital. Numerous techniques have been suggested for WIP reduction, and CONWIP is a competitive algorithm for WIP reduction. Prior CONWIP algorithms have been primarily sequential algorithms and can be potentially incur significant computing time, especially when dealing with inventories for multiple products. The paper proposes a card-setting algorithm for multiple product types subject to routing and throughput requirements. The proposed algorithm searches the WIP space iteratively and the step-size is adaptively selected based on the known properties of multi-chain, multi-class, closed queuing networks. Furthermore, parallelization of this search algorithm across multiple processors is proposed where each processor searches a different segment of the WIP space while adaptively adjusting its step size for all product types to ensure fast convergence. The proposed parallel algorithm can take advantage of distributed computing architectures to speed-up the overall computation. An experimental implementation of the parallel algorithm using Message Passing Interface (MPI) over a high-speed network is described. Computational results demonstrate that the proposed parallel algorithm can be parallelized over eight to ten processors to obtain a speed-up of three to five.