Dual gradient method for linearly constrained, strongly convex, separable mathematical programming problems

DOI10.1007/BF00939216zbMath0595.90069OpenAlexW2016799959MaRDI QIDQ1078076

B. George

Publication date: 1987

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

Full work available at URL: https://doi.org/10.1007/bf00939216

zbMATH Keywords

computational resultsstrongly convexconvergence proofsdual gradient methodlinearly constrainedseparable mathematical programming

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Methods of successive quadratic programming type (90C55)

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Cites Work

• A Newton method for convex separable network flow problems
• A scaled reduced gradient algorithm for network flow problems with convex separable costs
• Solving the Pipe Network Analysis Problem Using Optimization Techniques
• Dualität und Approximation bei konvexen Optimierungsproblemen
• Duality in Nonlinear Programming: A Simplified Applications-Oriented Development

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