Complete decomposition algorithm for nonconvex separable optimization problems and applications

DOI10.1016/0005-1098(92)90069-RzbMath0770.90066OpenAlexW2008128853MaRDI QIDQ1195824

Shin-Yeu Lin

Publication date: 4 January 1993

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0005-1098(92)90069-r

zbMATH Keywords

parallel computationrecursive quadratic programmingcomplete decomposition algorithmnonconvex separable optimization

Mathematics Subject Classification ID

Nonlinear programming (90C30) Decomposition methods (49M27)

Related Items (3)

Decomposition Methods Based on Augmented Lagrangians: A Survey ⋮ Two-level primal-dual proximal decomposition technique to solve large scale optimization problems ⋮ Decomposition for structured convex programs with smooth multiplier methods

Cites Work

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• A globally convergent method for nonlinear programming
• Decomposition in large system optimization using the method of multipliers
• Convexification procedures and decomposition methods for nonconvex optimization problems
• New dual-type decomposition algorithm for non-convex separable optimization problems
• A new technique for nonconvex primal-dual decomposition of a large-scale separable optimization problem
• New algorithms for unconstrained nonlinear optimal control problems
• A hardware implementable two-level parallel computing algorithm for general minimum-time control
• Superlinearly convergent variable metric algorithms for general nonlinear programming problems
• On the Use of Approximations in Algorithms for Optimization Problems with Equality and Inequality Constraints

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