A superlinearly and quadratically convergent SQP type feasible method for constrained optimization

DOI10.1007/s11766-000-0057-9zbMath0988.90051OpenAlexW2320608532MaRDI QIDQ1589812

Shengjia Xue, Jin-Bao Jian, Ke-Cun Zhang

Publication date: 16 July 2002

Published in: Applied Mathematics. Series B (English Edition) (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11766-000-0057-9

zbMATH Keywords

convergencerate of convergenceconstrained optimizationSQPfeasible method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Methods of successive quadratic programming type (90C55)

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New sequential quadratically-constrained quadratic programming method of feasible directions and its convergence rate, A modified SQP algorithm for minimax problems, A method combining norm-relaxed QP subproblems with systems of linear equations for constrained optimization, A sequential quadratic programming algorithm for nonlinear minimax problems, A new superlinearly convergent norm-relaxed method of strongly sub-feasible direction for inequality constrained optimization, A strongly convergent norm-relaxed method of strongly sub-feasible direction for optimization with nonlinear equality and inequality constraints, A New Superlinearly Convergent Strongly Subfeasible Sequential Quadratic Programming Algorithm for Inequality-Constrained Optimization, A sequential quadratically constrained quadratic programming method of feasible directions, An SQP feasible descent algorithm for nonlinear inequality constrained optimization without strict complementarity, A new feasible descent algorithm combining SQP with generalized projection for optimization problems without strict complementarity, A feasible descent SQP algorithm for general constrained optimization without strict complemen\-tar\-ity, An active set sequential quadratic programming algorithm for nonlinear optimisation

Cites Work

• Robust recursive quadratic programming algorithm model with global and superlinear convergence properties
• A Superlinearly Convergent Feasible Method for the Solution of Inequality Constrained Optimization Problems
• New Results on a Continuously Differentiable Exact Penalty Function
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