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Erschienen in:
1994 | OriginalPaper | Buchkapitel
Restarting Strategies for the DQA Algorithm
verfasst von : Adam J. Berger, John M. Mulvey, Andrzej Ruszczyński
Erschienen in: Large Scale Optimization
Verlag: Springer US
Enthalten in: Professional Book Archive
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A scenario-based decomposition algorithm is proposed for large stochastic pro-grams. The subproblem clusters consisting of separable quadratic programs are solved by means of a nonlinear interior point algorithm. Critical implementation issues are analyzed, including restarting and alternative splitting strategies. The approach is suited to a distributed multicomputer such as a network of workstations. Testing with several large LPs (117,000 constraints and 276,000 variables) shows the efficiency of the concepts.