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CONLIN: An efficient dual optimizer based on convex approximation concepts

Fleury, C

Structural Optimization, 1989-06, Vol.1 (2), p.81-89 [Periódico revisado por pares]

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Título:
CONLIN: An efficient dual optimizer based on convex approximation concepts
Autor: Fleury, C
É parte de: Structural Optimization, 1989-06, Vol.1 (2), p.81-89
Notas: ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
Descrição: A dual optimizer for solving the explicit subproblem generated by the Convex Linearization method strategy is proposed which performs most of the computations in the iterative process with small sets of primal variables and dual variables. The method involves the determining of the maximum of the dual function in a sequence of dual subspaces of variable dimensionality, and the replacing of the primary dual problem itself with a sequence of approximate quadratic subproblems which have nonnegativity constraints on the dual variables. It is noted that because each of the quadratic subproblems is restricted to the current subspace of nonzero dual variables, its dimensionality is usually reasonably small. (R.R.)
Idioma: Inglês

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