Convexification and decomposition of separable nonconvex optimization problems

DOI10.1080/02331939208843843zbMath0817.90105OpenAlexW2062235746MaRDI QIDQ4327962

B. Engelmann

Publication date: 27 March 1995

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331939208843843

zbMATH Keywords

decompositionconvexificationcoordinationsecond-order sufficient optimality conditionsaugmented Lagrangianadditive separable, nonconvex optimizationmultiplier shift

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30)

Cites Work

• Two-level primal-dual decomposition technique for large-scale nonconvex optimization problems with constraints
• Decomposition in large system optimization using the method of multipliers
• Convexification procedures and decomposition methods for nonconvex optimization problems
• The use of Hestenes' method of multipliers to resolve dual gaps in engineering system optimization
• A new technique for nonconvex primal-dual decomposition of a large-scale separable optimization problem
• Applications of the method of partial inverses to convex programming: Decomposition
• Application of the method of multipliers to state space constrained optimal control problems with discrete time
• Augmented Lagrange Multiplier Functions and Duality in Nonconvex Programming
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