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A reformulation of the aggregate planning problem
Author(s) -
Schroeder Roger G.,
Larson Paul D.
Publication year - 1986
Publication title -
journal of operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.649
H-Index - 191
eISSN - 1873-1317
pISSN - 0272-6963
DOI - 10.1016/0272-6963(86)90001-x
Subject(s) - aggregate planning , production (economics) , aggregate (composite) , staffing , production planning , service (business) , overtime , set (abstract data type) , operations research , computer science , service level , economics , business , marketing , operations management , microeconomics , mathematics , materials science , management , labour economics , programming language , composite material
This article proposes a reformulation of the aggregate planning problem which more closely agrees with situations frequently encountered in practice. The proposed reformulation assumes that a firm's production planners want to determine the expected service and inventory levels for a given production profile in the face of uncertain seasonal demand. By using several different production profiles that are each consistent with the firm's staffing, subcontracting, and overtime policies, it is possible to pick the profile that best meets the firm's preferences for service level and inventory turns. Actually, the trade‐offs between inventory and service levels are examined so that an informed choice can be made by all of those concerned. One of the advantages of the proposed model is that communications can be established among production, marketing, and finance managers who often have conflicting goals. Also, levels for inventory turns, service, and production can be set that are consistent with each other. Furthermore, several alternative production profiles can be examined in a relatively short time through the use of the simulation model proposed. An application of the model to the Wagner Spray Tech Company, a producer of painting equipment, is presented. In this particular case, where forecasting errors are quite high, some of the potential uses of the model are presented. Also, reasons are given why this particular reformulation of the aggregate planning problem was found to be useful.