Monotone splitting sequential quadratic optimization algorithm with applications in electric power systems

DOI10.1007/s10957-020-01697-8zbMath1461.65160OpenAlexW3037596826MaRDI QIDQ779870

Guodong Ma, Jin-Bao Jian, Linfeng Yang, Jianghua Yin, Chen Zhang

Publication date: 14 July 2020

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-020-01697-8

zbMATH Keywords

splitting algorithmelectric power systemslinear equality and box constraintssequential quadratic optimizationtwo-block nonconvex optimization

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Methods of successive quadratic programming type (90C55)

Related Items (5)

Convergence analysis of an improved Bregman-type Peaceman-Rachford splitting algorithm for nonconvex nonseparable linearly constrained optimization problems ⋮ A symmetric splitting sequential quadratic optimization algorithm for two-block nonlinearly constrained nonconvex optimization ⋮ Convergence analysis of an ALF-based nonconvex splitting algorithm with SQP structure ⋮ A QCQP-based splitting SQP algorithm for two-block nonconvex constrained optimization problems with application ⋮ A superlinearly convergent splitting feasible sequential quadratic optimization method for two-block large-scale smooth optimization

Uses Software

• OPTI
• BADMM

Cites Work

• Unnamed Item
• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Fast alternating linearization methods for minimizing the sum of two convex functions
• An efficient feasible SQP algorithm for inequality constrained optimization
• Global convergence of an SQP method without boundedness assumptions on any of the iterative sequences
• Global convergence of ADMM in nonconvex nonsmooth optimization
• On non-ergodic convergence rate of Douglas-Rachford alternating direction method of multipliers
• Regularized Jacobi-type ADMM-methods for a class of separable convex optimization problems in Hilbert spaces
• On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
• A Strictly Contractive Peaceman--Rachford Splitting Method for Convex Programming
• Convergence Study on the Symmetric Version of ADMM with Larger Step Sizes
• On the Numerical Solution of Heat Conduction Problems in Two and Three Space Variables
• Global Convergence of Splitting Methods for Nonconvex Composite Optimization
• A New Superlinearly Convergent Strongly Subfeasible Sequential Quadratic Programming Algorithm for Inequality-Constrained Optimization
• A successive quadratic programming algorithm with global and superlinear convergence properties
• A Superlinearly Convergent Feasible Method for the Solution of Inequality Constrained Optimization Problems
• Splitting Algorithms for the Sum of Two Nonlinear Operators
• Fast Alternating Direction Optimization Methods
• Iteration-Complexity of Block-Decomposition Algorithms and the Alternating Direction Method of Multipliers

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