A scenario-based stochastic programming approach for technology and capacity planning

Authors:
Zhi-Long Chen;Shanling Li;Devanath Tirupati
Affiliations:
Department of Systems Engineering, University of Pennsylvania, Philadelphia, PA;Faculty of Management, McGill University, Montreal, PQ, Canada;Indian Institute of Management, Ahmedabad, India
Venue:
Computers and Operations Research
Year:
2002

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ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I

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Abstract

In response to market pressures resulting in increased competition, product proliferation and greater customization, firms in many industries have adopted modern technologies to provide operational flexibility on several dimensions. In this paper, we consider the role of product mix flexibility, defined as the ability to produce a variety of products, in an environment characterized by multiple products, uncertainty in product life cycles and dynamic demands. Using a scenario-based approach for capturing the evolution of demand, we develop a stochastic programming model for determining technology choices and capacity plans. Since the resulting model is likely to be large and may not be easy to solve with standard software packages, we develop a solution procedure based on augmented Lagrangian method and restricted simplicial decomposition. The scope of our approach for deriving context specific managerial insights is illustrated by the results of limited computations. Finally, we demonstrate the versatility of our approach by deriving a special case of the general model to address some tactical issues related to new product introduction.