Short-term production scheduling: A new and more efficient algorithm and its application to pulp and paper industry

In this paper a new quadratic-programming problem (based on the cost function of the control deviations only) and a new optimization method (based on a three-level goal coordination algorithm intended to solve the singular problem obtained with the criterion used) are developed and tested. They are a new approach to the short-term production scheduling in industrial complexes (with an application to a pulp and paper mill) solved before by Tamura’s two-level algorithm with gradient coordination. It is shown that the new approach substantially reduces (60 times in the numerical example) the computational cost by avoiding the necessity of using an ill-defined quadratic performance criterion and reducing the number of optimization variables through the grouping concept issued from the fundamental properties of the optimal solution. Numerical examples illustrate the authors’ current experience with the new approach. The new approach gives production plans of higher quality from an industrial point of view, and it is (in the authors’ opinion) a significant contribution to building friendly and interactive decision support systems for production control and optimization.