A quadratically approximate framework for constrained optimization, global and local convergence

DOI10.1007/s10114-007-4465-0zbMath1191.90068OpenAlexW2146325318MaRDI QIDQ943517

Jin-Bao Jian

Publication date: 9 September 2008

Published in: Acta Mathematica Sinica. English Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10114-007-4465-0

zbMATH Keywords

constrained optimizationglobal and local convergencequadratic approximationquadratic constraintsalgorithm framework

Mathematics Subject Classification ID

Related Items (6)

Quadratically constraint quadratical algorithm model for nonlinear minimax problems ⋮ A method combining norm-relaxed QCQP subproblems with active set identification for inequality constrained optimization ⋮ A working set SQCQP algorithm with simple nonmonotone penalty parameters ⋮ Simple sequential quadratically constrained quadratic programming feasible algorithm with active identification sets for constrained minimax problems ⋮ A superlinearly convergent SQP method without boundedness assumptions on any of the iterative sequences ⋮ A sequential quadratically constrained quadratic programming method for unconstrained minimax problems

Uses Software

• SNOPT
• SOCP

Cites Work

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• Nonlinear programming without a penalty function.

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