An SQP feasible descent algorithm for nonlinear inequality constrained optimization without strict complementarity
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Publication:2485397
DOI10.1016/j.camwa.2004.09.004zbMath1075.90072OpenAlexW2023346104MaRDI QIDQ2485397
Publication date: 4 August 2005
Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.camwa.2004.09.004
Programming involving graphs or networks (90C35) Methods of successive quadratic programming type (90C55)
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Cites Work
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- The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function. I. Convergence analysis
- More test examples for nonlinear programming codes
- Test examples for nonlinear programming codes
- A globally convergent method for nonlinear programming
- Robust recursive quadratic programming algorithm model with global and superlinear convergence properties
- A generalized projection-successive linear equations algorithm for nonlinearly equality and inequality constrained optimization and its rate of convergence
- A superlinearly and quadratically convergent SQP type feasible method for constrained optimization
- Quadratically and superlinearly convergent algorithms for the solution of inequality constrained minimization problems
- Exact penalty function algorithm with simple updating of the penalty parameter
- On combining feasibility, descent and superlinear convergence in inequality constrained optimization
- Avoiding the Maratos Effect by Means of a Nonmonotone Line Search I. General Constrained Problems
- A successive quadratic programming algorithm with global and superlinear convergence properties
- A recursive quadratic programming algorithm that uses differentiable exact penalty functions
- A Superlinearly Convergent Feasible Method for the Solution of Inequality Constrained Optimization Problems
- A QP-Free, Globally Convergent, Locally Superlinearly Convergent Algorithm for Inequality Constrained Optimization
- A surperlinearly convergent algorithm for constrained optimization problems
- Avoiding the Maratos Effect by Means of a Nonmonotone Line Search. II. Inequality Constrained Problems—Feasible Iterates
- Superlinearly convergent variable metric algorithms for general nonlinear programming problems
- Sequential Quadratic Programming with Penalization of the Displacement
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