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A linearisation of the maximum entropy formalism using separable programming

Author

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  • Ermanno Affuso
  • Steven B. Caudill

Abstract

The maximum entropy principle is a standard tool for the calibration of non-linear programming models which are frequently used for policy analysis. The information entropy function is concave and separable. In this paper, we derive a linear approximation of the entropy using separable programming. As we demonstrate, our linear entropy formulation is useful for the calibration of separable non-linear models of very large scale. To demonstrate, we solve both an ill-posed and a well-posed inverse problem and we analyse the sensitivity of the results on the number of breakpoints of the piecewise linear approximation.

Suggested Citation

  • Ermanno Affuso & Steven B. Caudill, 2015. "A linearisation of the maximum entropy formalism using separable programming," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 22(4), pages 385-404.
    • Handle: RePEc:ids:ijores:v:22:y:2015:i:4:p:385-404
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