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filterSQP

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The solver filterSQP solves large, sparse or dense linear, quadratic and nonlinear programming problems.

Main features

  • The solver filterSQP is a Sequential Quadratic Programming solver suitable for solving large, sparse or dense linear, quadratic and nonlinear programming problems. The method avoids the use of penalty functions. Global convergence is enforced through the use of a trust--region and the new concept of a ''filter'' which accepts a trial point whenever the objective or the constraint violation is improved compared to all previous iterates. The size of the trust--region is reduced if the step is rejected and increased if it is accepted (provided the agreement between the quadratic model and the nonlinear functions is sufficiently good). The QP subproblems are solved using bqpd.
     
  • filterSQP needs second order information for the objective function and the nonlinear constraints. Tomlab estimates any unknown derivatives, but the accuracy and convergence may be worse in such cases.
     
  • The dense and the sparse version of filterSQP are compiled in two different Mex binaries, making the two versions optimally efficient.
     
  • filterSQP is integrated with the TOMLAB driver routines.
     
  • filterSQP may be used as subproblem solver in the TOMLAB environment.
     

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