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

Operations Research · 2002 · Volume 50 · Issue 4

Abstract

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.

Keywords

Production planning: product cycling with yield uncertainty. Production application: process industry, food-processing sector . Production heuristics: Lagrangian heuristic, operational heuristic

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