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Constraint aggregation principle in convex optimization
Ermoliev, Yuri M.
Kryazhimskii, Arkadii V.
Ruszczynski, Andrzej

Data: 1997
Resum: A general constraint aggregation technique is proposed for convex optimization problems. At each iteration a set of convex inequalities and linear equations is replaced by a single surrogate inequality formed as a linear combination of the original constraints. After solving the simplified subproblem, new aggregation coefficients are calculated and the iteration continues. This general aggregation principle is incorporated into a number of specific algorithms. Convergence of the new methods is proved and speed of convergence analyzed. Next, dual interpretation of the method is provided and application to decomposable problems is discussed. Finally, a numerical illustration is given. .
Llengua: Anglès.
Document: Article ; recerca ; article ; publishedVersion
Matèria: Nonsmooth optimization ; Surrogate constraints ; Subgradient methods ; Decomposition
Publicat a: Mathematical Programming, vol. 76 n. 3 (1997) p. 353-372, ISSN 0025-5610



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