A linearisation of the maximum entropy formalism using separable programming
by Ermanno Affuso; Steven B. Caudill
International Journal of Operational Research (IJOR), Vol. 22, No. 4, 2015

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.

Online publication date: Sat, 09-May-2015

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