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nlpSolve

Solves general linear and nonlinear programming problems.

Main features:

  • nlpSolve is a Matlab implementation of the Filter SQP by Roger Fletcher and Sven Leyffer, Nonlinear Programming without a penalty function, Dundee NA/171, 1997.
  • It is an advantage if the user can supply a routine to compute the second derivatives of the constraints.
  • nlpSolve is using second order information, if available and is using a general problem formulation with lower/upper bound format, It is an advantage if the user can supply a routine to compute the second derivatives of the constraints.
  • The user can select to run either the standard Filter SQP or a quasi-Newton BFGS Filter SQP, estimating the Hessian matrix using only the gradient information. If the gradient is estimated numerically, the user must select to use the BFGS, otherwise numerical problems are likely.
  • In Tomlab /MINOS nlpSolve is using QPOPT (or MINOS) as QP solver giving speed and robustness.
  • It has explicit treatment of simple bounds, linear and nonlinear constraints.
  • The Filter SQP algorithm is also available in the TOMLAB /MINLP toolbox as filterSQP, a Fortran version written by Fletcher and Leyffer.

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