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IMA Journal of Management Mathematics Advance Access originally published online on March 6, 2007
IMA Journal of Management Mathematics 2008 19(1):87-97; doi:10.1093/imaman/dpm006
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© The authors 2007. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Modelling history-dependent parameters in the SMPS format for stochastic programming

H. I. Gassmann{dagger}

School of Business Administration, Dalhousie University, Halifax, Canada

G. Infanger

Management Science and Engineering, Stanford University, Stanford, CA

{dagger} Email: Horand.Gassmann{at}dal.ca

Received on 1 October 2004. Accepted on 31 January 2007.

This paper proposes two extensions to the SMPS format for stochastic programs to permit modelling of autoregressive-moving average (ARMA) processes. Sampling-based algorithms can thus proceed independently of any underlying modelling system, increasing efficiency. An illustrative example demonstrates the power of the new constructs.

Keywords: stochastic programming; SMPS format; model representation; ARMA models; history-dependent distributions


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