Product Cycling With Uncertain Yields: Analysis and Application to the Process Industry

We formulate the dynamic product-cycling problem with yield uncertainty and buffer limits to determine how much product to produce at what time to minimize total expected switching, production, inventory storage, and backorder costs. A “restricted” Lagrangian technique is used to develop a lower bound and a model-based Lagrangian heuristic. We also develop an operational heuristic and a greedy heuristic. The operational heuristic has been implemented at seven refineries at Cerestar, Europe’s leading manufacturer of wheat-and corn-based starch products in the food-processing industry. This has already reduced total costs by around 5 percent or $3 million annually at these sites. Tests of the Lagrangian heuristic on data from these refineries during this period have shown the potential to further reduce total costs by at least 2 percent or about $1 million. In addition, the Lagrangian heuristic has provided an objective basis to evaluate the economic impact of several strategic decisions involving issues such as buffer expansion, variability reduction, and product selection.