RESEARCH PAPERS: Design Automation Papers

Resizing: Predicting a New Geometric Programming Optimum as Coefficients Vary

[+] Author and Article Information
D. J. Wilde

Design Division, Mechanical Engineering Dept., Stanford University, Stanford, Calif. 94305

J. Mech., Trans., and Automation 106(1), 11-16 (Mar 01, 1984) (6 pages) doi:10.1115/1.3258549 History: Received June 10, 1983; Online November 19, 2009


Imagine that an optimal solution is available for a constrained geometric program, and suppose one wishes a satisfactory solution for greatly different values of some of the coefficients. An estimate can be constructed by using the values of the dual variables for the old optimum in the invariance conditions for the new problem. Although these are inconsistent except at the precise optimum, a unique primal solution can easily be generated from them by the method of least squares with individual equations weighted by the value of the corresponding dual variable. The matrix equations for these linear operations are derived and applied to a well-known merchant fleet design problem. The predictions are remarkably accurate—1.4 percent error for a 100 percent coefficient change.

Copyright © 1984 by ASME
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