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Robust Capacity Planning in Semiconductor Manufacturing

Francisco Barahona (barahon***at***us.ibm.com)
Stuart Bermon (Bermon***at***us.ibm.com)
Oktay Gunluk (oktay***at***watson.ibm.com)
Sarah Hood (sarahood***at***us.ibm.com)

Abstract: We present a stochastic programming approach to capacity planning under demand uncertainty in semiconductor manufacturing. Given multiple demand scenarios together with associated probabilities, our aim is to arrive at a set of tools that does well across all of these scenarios. We formulate the problem as a mixed-integer program in which expected value of the unmet demand is minimized subject to capacity and budget constraints. This is a difficult two-stage stochastic mixed-integer program which can be solved to near-optimality with the help of cutting planes and limited enumeration. Analyses of the results in some real-life situations are also presented.

Keywords: capacity planning, stochastic integer programming

Category 1: Applications -- OR and Management Sciences (Supply Chain Management )

Citation: IBM report RC22196

Download: [Postscript][PDF]

Entry Submitted: 10/03/2001
Entry Accepted: 10/03/2001
Entry Last Modified: 04/17/2005

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