Restarting Strategies for the DQA Algorithm

Adam J. Berger, John M. Mulvey and Andrzej Ruszczyński
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Adam J. Berger: School of Engineering and Applied Science, Princeton University, Department of Civil Engineering and Operations Research
John M. Mulvey: School of Engineering and Applied Science, Princeton University, Department of Civil Engineering and Operations Research
Andrzej Ruszczyński: International Institute for Applied Systems Analysis

A chapter in Large Scale Optimization, 1994, pp 1-25 from Springer

Abstract: Abstract 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.

Keywords: stochastic programming; large-scale linear program; decomposition; parallel computation (search for similar items in EconPapers)
Date: 1994
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DOI: 10.1007/978-1-4613-3632-7_1

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