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Verification of Linear Programming Solutions, with Emphasis on Supply Implications*

Published online by Cambridge University Press:  28 April 2015

C. Richard Shumway  and
Hovav Talpaz
C. Richard Shumway
Affiliation:
Texas A & M University
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Extract

Linear programming (LP) models have been developed for a wide range of normative purposes in agricultural production economics. Despite their widespread application, a pervading concern among users is reliability — how well does a particular model actually describe and/or predict real world phenomena when it is so designed.

Much attention has been devoted in recent years to methods for making programming models produce results more in line with those actually observed. These efforts have included development of more detail in production activities and restrictions, incorporation of flexibility constraints into recursive programming systems, specification of more realistic behavioral properties, and development of guidelines for reducing aggregation error.

Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 9 , Issue 2 , December 1977 , pp. 1 - 8
Copyright
Copyright © Southern Agricultural Economics Association 1977

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Footnotes

*

Technical Article 12738 of the Texas Agricultural Experiment Station. This paper is a revised and expanded version of “Combining LP Results and Time Series Data for Prediction of Supply: Two Approaches,” contributed paper presented at AAEA annual meeting. State College, Pennsylvania, 15-18 August, 1976. The authors wish to thank Peter Barry, John Penson, C. Robert Taylor and anonymous Journal reviewers for constructive comments on earlier drafts. Anne Chang provided much computer assistance for which we are most appreciative.

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