A prototype decision support system for strategic planning under uncertainty

Strategic planning of the supply chain is an important decision problem determining the long‐term survival and prosperity of companies in the manufacturing, retail, and other industrial sectors. In general such companies rely on their information systems to acquire the essential data that are used in their planning models. The interaction of information systems and decision modelling, and the progressive transformation of data, into information, and knowledge is a key process underlying any decision support system (DSS) for strategic, tactical or operational planning. In this paper we consider a DSS for supply chain planning (SCP) decisions. The SCP system has an embedded decision engine that uses a two‐stage stochastic program as a paradigm for optimisation under uncertainty. The system has been used for decision making in diverse domains, including automotive manufacturing and consumer products.

[1]  Hau L. Lee,et al.  Strategic Analysis of Integrated Production-Distribution Systems: Models and Methods , 1988, Oper. Res..

[2]  Jack Dongarra,et al.  PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing , 1995 .

[3]  Douglas J. Thomas,et al.  Coordinated supply chain management , 1996 .

[4]  Eduardo Marco Modiano,et al.  Derived Demand and Capacity Planning Under Uncertainty , 1987, Oper. Res..

[5]  Gautam Mitra,et al.  A model for strategic planning under uncertainty , 1996 .

[6]  Andrew B. Whinston,et al.  The environment approach to decision support , 1988 .

[7]  Gloria Pérez,et al.  O(n log n) procedures for tightening cover inequalities , 1999, Eur. J. Oper. Res..

[8]  Anna Sciomachen,et al.  Local search procedures for improving feasible solutions to the sequential ordering problem , 1993, Ann. Oper. Res..

[9]  Laureano F. Escudero,et al.  Production planning via scenario modelling , 1993, Ann. Oper. Res..

[10]  Gautam Mitra,et al.  RISK AND RETURN ANALYSIS OF A MULTI­ PERIOD STRATEGIC PLANNING PROBLEM , 1997 .

[11]  A. M. Geoffrion,et al.  Multicommodity Distribution System Design by Benders Decomposition , 1974 .

[12]  Gautam Mitra,et al.  Mathematical Models for Decision Support , 1987, NATO ASI Series.

[13]  Linus Schrage,et al.  OR Practice - A Scenario Approach to Capacity Planning , 1989, Oper. Res..

[14]  Gautam Mitra,et al.  Adapting on-line analytical processing for decision modelling: the interaction of information and decision technologies , 1999, Decis. Support Syst..

[15]  Gautam Mitra,et al.  Computational solution of capacity planning models under uncertainty , 2000, Parallel Comput..

[16]  Laureano F. Escudero,et al.  Schumann, a modeling framework for supply chain management under uncertainty , 1999, Eur. J. Oper. Res..

[17]  Jeremy F. Shapiro,et al.  Optimizing Resource Acquisition Decisions by Stochastic Programming , 1988 .

[18]  Alexei A. Gaivoronski,et al.  Decomposition Methods for Network Optimization Problems in the Presence of Uncertainty , 1997 .

[19]  Gerald G. Brown,et al.  Design and operation of a multicommodity production/distribution system using primal goal decomposition , 1987 .

[20]  Warren B. Powell,et al.  Models and Algorithms for Distribution Problems with Uncertain Demands , 1996, Transp. Sci..

[21]  Oded Berman,et al.  Models for planning capacity expansion of convenience stores under uncertain demand and the value of information , 1995, Ann. Oper. Res..

[22]  Gilbert Laporte,et al.  The Vehicle Routing Problem with Stochastic Travel Times , 1992, Transp. Sci..

[23]  Harvey J. Greenberg,et al.  Views of mathematical programming models and their instances , 1995, Decis. Support Syst..

[24]  Awi Federgruen,et al.  A Combined Vehicle Routing and Inventory Allocation Problem , 1984, Oper. Res..