Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming
STANFORD UNIV CA SYSTEMS OPTIMIZATION LAB
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The purpose of this paper is to describe a Generalized Reduced Gradient GRG algorithm for nonlinear programming, its implementation as a FORTRAN program for solving small to medium size problems, and some computational results. Our focus is more on the software implementation of the algorithm than on its mathematical properties. This is in line with the premise that robust, efficient, easy to use NLP software must be written and made accessible if nonlinear programming is to progress, both in theory and in practice.
- Operations Research
- Computer Programming and Software