A Noniterative Algorithm for the Multiproduct Production and Work Force Planning Problem

Discrete optimal control theory is used to develop an efficient noniterative algorithm for solving the multiproduct production and work force planning problems with a quadratic cost function. The quadratic cost models allow uncertainties to be handled directly because they minimize the expected cost if unbiased expected demand forecasts are given. A real-world problem may involve as many as 200,000 variables. The noniterative algorithm makes the computations, irrespective of the number of products, not only feasible but also extremely easy and efficient.