Flow control in time-varying, random supply chains

This paper focuses on the logistics aspect of supply chain management. It proposes a randomized flow management algorithm for a time-varying, random, supply chain network. A constrained stochastic optimization problem that maximizes the profit function in terms of the long-run, time-average of the flows in the supply chain is formulated. The algorithm is distributed and based on queueing theory and stochastic Lyapunov analysis concepts. The long-run, time averages of the flows generated by the algorithm can get arbitrarily close to the solution of the aforementioned optimization problem. In support of the theoretical results, numerical simulations are also presented.