Abstract
In dynamic programming and decomposition methods one often applies an iterated minimization procedure. The problem variables are partitioned into several blocks, say x and y. Treating y as a parameter, the first phase consists of minimization with respect to the variable x. In a second phase the minimization of the resulting optimal value function depending on y is considered. In this paper we treat this basic idea on a local level. It turns out that strong stability (in the sense of Kojima) in the first phase is a natural assumption. In order to show that the iterated local minima of the parametric problem lead to a local minimum for the whole problem, we use a generalized version of a positive definiteness criterion of Fujiwara-Han-Mangasarian.
Original language | Undefined |
---|---|
Pages (from-to) | 679-691 |
Journal | Mathematics of operations research |
Volume | 11 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1986 |
Keywords
- IR-98548