Production Planning of Style Goods with High Setup Costs and Forecast Revisions

Gabriel R. Bitran, Elizabeth A. Haas and Hirofumi Matsuo
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Gabriel R. Bitran: Massachusetts Institute of Technology, Cambridge, Massachusetts
Elizabeth A. Haas: McKinsey and Company, Inc., Cleveland, Ohio

Operations Research, 1986, vol. 34, issue 2, 226-236

Abstract: In this paper we study a problem, common to a wide variety of manufacturing companies, of determining the production schedule of style goods, such as clothing and consumer durables, under capacity constraints. Demand for items is stochastic and occurs in the last season of the planning horizon. Demand estimates are revised in each period. We exploit the problem's two-level hierarchical structure, which is characterized by families and items. Production changeover costs from one family to another are high, compared to other costs. However, changeover costs between items in the same family are negligible. We first formulate this problem as a difficult-to-solve stochastic mixed integer programming problem. Then, exploiting the problem's hierarchical structure, we formulate a deterministic, mixed integer programming problem and solve it by means of an algorithm that provides an approximate solution. A lower bound is obtained by applying generalized linear programming to the approximate problem. We illustrate the procedure using the disguised data of a consumer electronics company. The computational results demonstrate the effectiveness of the proposed approach in a practical setting.

Keywords: 291 production of style goods; 331 production with high setup costs; 621 stochastic programming (search for similar items in EconPapers)
Date: 1986
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Citations: View citations in EconPapers (29)

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