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NLPMMX: A Fortran Implementation of an SQP Algorithm for
Min-Max Optimization -
User's Guide
K. Schittkowski, Report, Department of Computer Science, University of Bayreuth (2007)
The Fortran subroutine NLPMMX solves constrained min-max nonlinear programming problems, where the maximum of absolute nonlinear function values is to be minimized. It is assumed that all functions are continuously differentiable. By introducing one additional variable and nonlinear equality constraints, the problem is transformed into a general smooth nonlinear program subsequently solved by the sequential quadratic programming (SQP) code NLPQLP. Some comparative numerical results are included, the usage of the code is documented, and two illustrative examples are presented.
To download the report, click here: nlpmmx.pdf