Nonlinear Programming with very Many Constraints
Version 2.6 (2012)
The user defines the maximum number of lines in the matrix of the linearized constraints, that can be stored in core. By investigating the constraint function values, a decision is made which restrictions are necessary to fill that matrix. The algorithm will stop, if too many constraints are violated.
NLPQLB is implemented within the structural mechanical optimization system LAGRANGE at EADS to solve large structural design optimization problems.
- K. Schittkowski, Solving nonlinear programming problems with very many constraints, Optimization, Vol. 25, 179-196 (1992)
- K. Schittkowski, NLPQLB: A Fortran implementation of an SQP algorithm with active set strategy for solving optimization problems with a very large number of nonlinear constraints - user's guide, version 2.0, Report, Department of Computer Science, University of Bayreuth
- K. Schittkowski, An active set strategy for solving optimization problems with up to 200,000,000 nonlinear constraints, submitted for publication