The Kellogg Company Optimizes Production, Inventory and Distribution
For over a decade, The Kellogg Company has used its planning system (KPS) a large-scale multiperiod linear program, to guide production and distribution decisions for its cereal and convenience food business. An operational version of KPS, at a weekly level of detail, helps determine where products are produced and how finishedproducts and in process products are shipped between plants and distribution centers. A tactical version of KPS, at a monthly level of detail, helps to establish plant budgets and make capacity expansion and consolidation decisions. Operational KPS reduced production, inventory, and distribution costs by an estimated $4.5 million in 1995. Tactical KPS recently guided a consolidation of productioncapacity with a project savings of $35 to $40 million per year.
The Kellogg company has been using a large scale linear program, the Kellogg Planning System (KPS), for more than a decade to guide its operational, production, inventory, and distribution decisions for breakfast cereal and other foods. In addition, KPS help Kellog to make tactical decisions on budgeting, capacity expansion,capacity reassignment, and other similar issues.
KPS model Kellogs operations in the United States and Canada, with global operations under study. These operations include the production, inventory, and distribution of hundreds of items from Kellogg-owned and contracted plants out to distribution centers and to costumers.
The Kellogg company had long used spreadsheets and special software for materialsrequirements planning and distribution resource planning. But 1987 Kellogg realized that its expanding product line and geographically dispersed production facilities required some means of systematic, global coordination and optimization. KPS was the result. After a year of development, we installed prototypic software in 1989. Although KPS was intended primarly for operational planning, theprocess of initial testing inspired the first real applications, which were tactical. For example, Kellogg was adding a new production facility to expand capacity and extend the product line and it used KPS to compare the overall cost implications of locating that facility in one existing plant versus another.
The tactical linear program
Even though we originally envisaged KPS as only anoperational model, we have also developed a tactical version of KPS for long range planning, on the order of 12 to 24 months. Kellogs uses long range planning to develop plant budgets, investigate capacity-expansion issues, test new DC locations for cost savings, and so on. The tactical model is identical to the operational one except that (1) time perids consist of four week blocks called months, (2)transportation is typically treated as instantaneous, and (3) a special time cascade solution technique helps deal with the limited product shelf lives. Aggregating data and changing transportation delays is straightforward, but handling shelf lives is not. Kellogg wants to ship fresh products and, as a rule, products should reach customers within four or five months of production so that they haveplenty of shelf life remaining. Shelf life can essentially be ignored ina 16 month tactical model: if solved as a monolith, a 16 month version of KPS could, conceivably, call for producing an sku in month 1 to meet a demand in month 16, and this would not be realistic.
Conceptually, it is not hard to model a production, inventory, and distribution system that tracks the age 8or the use before date)of inventory: If the useful life of a product is t periods, create t copies of the inventory balance constraints, inventory variables, and shipping variables, and index them by the vintage of the product they represent. Unfortunately, this would increase the size of tactical kps nearly five-fold. Instead, we solve the standard model using a heuristic called a sliding time window.
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