Everything about Sequential quadratic programming

🧭 Start here: a 6-step reading path

1. Read the overview: Sequential quadratic programmingA 5-minute orientation
2. Skim a recent paper: Inequality constrained stochastic nonlinear optimization via active-set sequential quadratic programmingInfluential work since 2022
3. Pick up a classic book: Numerical optimizationThe most-reprinted book on the subject
4. Read the landmark paper: Sequential quadratic programming for large-scale nonlinear optimizationCited 230 times
5. Go sideways: Sequential linear-quadratic programmingA closely related topic
6. Go sideways: Mehrotra predictor–corrector methodA closely related topic

🏆 Landmark papers (most cited)

• Sequential quadratic programming for large-scale nonlinear optimization

  Paul T. Boggs, Jon W. Tolle · 2000 · Journal of Computational and Applied Mathematics · 230 citations

• A Globally Convergent Sequential Quadratic Programming Algorithm for Mathematical Programs with Linear Complementarity Constraints

  Masao Fukushima, Zhi-Quan Luo, Jong-Shi Pang · 1998 · Computational Optimization and Applications · 109 citations

• A piecewise linear chaotic map and sequential quadratic programming based robust hybrid particle swarm optimization

  Wenxing Xu, Zhiqiang Geng, Qunxiong Zhu · 2013 · Information Sciences · 37 citations

• Sequential quadratic programming for non‐linear elastic contact problems

  Gunnar Björkman, Anders Klarbring, Björn Sjödin · 1995 · International Journal for Numerical Methods in Engineering · 30 citations

• The sequential linear quadratic programming algorithm for solving dynamic optimization problems - a review.

  Sverre Støren, Terje Hertzberg · 1995 · Computers & Chemical Engineering · 25 citations

• Sequential penalty quadratic programming filter methods for nonlinear programming

  Pu-yan Nie · 2007 · Nonlinear Analysis: Real World Applications · 24 citations

• Sequential quadratic programming methods for parametric nonlinear optimization

  Vyacheslav Kungurtsev, Moritz Diehl · 2014 · Computational Optimization and Applications · 24 citations

• An efficient sequential quadratic programming algorithm for nonlinear programming

  Zhibin Zhu · 2005 · Journal of Computational and Applied Mathematics · 20 citations

🆕 Influential since 2022

• Inequality constrained stochastic nonlinear optimization via active-set sequential quadratic programming

  Sen Na, Mihai Anitescu, Mladen Kolar · 2023 · Mathematical Programming · 24 citations

• A Sequential Convex Programming Approach to Solving Quadratic Programs and Optimal Control Problems With Linear Complementarity Constraints

  Jonas Hall, Armin Nurkanović, Florian Messerer · 2022 · IEEE Control Systems Letters · 21 citations

• A quantum annealing-sequential quadratic programming assisted finite element simulation for non-linear and history-dependent mechanical problems

  Van-Dung Nguyen, Ling Wu, Françoise Remacle · 2024 · European Journal of Mechanics - A/Solids · 16 citations

• An effective nonlinear interval sequential quadratic programming method for uncertain inverse problems

  Jiachang Tang, Yong Lei, Taolin Zhang · 2023 · Structures · 12 citations

• A stabilized sequential quadratic semidefinite programming method for degenerate nonlinear semidefinite programs

  Yuya Yamakawa, Takayuki Okuno · 2022 · Computational Optimization and Applications · 11 citations

📚 Books worth reading

• Numerical optimizationJ. Frédéric Bonnans, Jean Charles Gilbert · 2003
• 📕Structural optimization with approximate sensitivitiesSurya N. Patnaik · 1994

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics

• Sequential linear-quadratic programming Sequential linear-quadratic programming (SLQP) is an iterative method for nonlinear optimization problems where objective function and constraints are…
• Mehrotra predictor–corrector method Mehrotra's predictor–corrector method in optimization is a specific interior point method for linear programming. It was proposed in 1989 by Sanjay Mehrotra…
• Noether's second theorem In mathematics and theoretical physics, Noether's second theorem relates symmetries of an action functional with a system of differential equations. The…
• Adjoint state method The adjoint state method is a numerical method for efficiently computing the gradient of a function or operator in a numerical optimization problem. It…
• Belinfante–Rosenfeld stress–energy tensor In mathematical physics, the Belinfante–Rosenfeld tensor is a modification of the stress–energy tensor that is constructed from the canonical stress–energy…
• Objective stress rate In continuum mechanics, objective stress rates are time derivatives of stress that do not depend on the frame of reference. Many constitutive equations…
• Regularization by spectral filtering Spectral regularization is any of a class of regularization techniques used in machine learning to control the impact of noise and prevent overfitting…
• Karush–Kuhn–Tucker conditions In mathematical optimization, the Karush–Kuhn–Tucker (KKT) conditions, also known as the Kuhn–Tucker conditions, are first derivative tests (sometimes…