Gradient methods of maximization of convex functions on discrete structures

DOI10.1007/BF01069426zbMath0607.90061OpenAlexW2091145635MaRDI QIDQ3747234

Michail M. Kovalev

Publication date: 1985

Published in: Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01069426

zbMATH Keywords

gradient methodsconvex discrete optimizationintegral programming

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Integer programming (90C10) Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming (90-02)

Cites Work

• Finding feasible vectors of Edmonds-Giles polyhedra
• Lower bounds on the worst-case complexity of some oracle algorithms
• Polyhedral aspects of discrete optimization
• Zur mathematischen theorie der optimalen standardisierung
• New applications of partial orders
• Best Algorithms for Approximating the Maximum of a Submodular Set Function
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