Journal
COMPUTATIONAL MANAGEMENT SCIENCE
Volume 6, Issue 2, Pages 117-133Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s10287-008-0087-y
Keywords
Stochastic programming; Scenario reduction; Scenario tree; Multistage
Categories
Funding
- DFG Research Center Matheon Mathematics for key technologies in Berlin
- BMBF [03SF0312E]
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A framework for the reduction of scenario trees as inputs of (linear) multistage stochastic programs is provided such that optimal values and approximate solution sets remain close to each other. The argument is based on upper bounds of the L-r-distance and the filtration distance, and on quantitative stability results for multistage stochastic programs. The important difference from scenario reduction in two-stage models consists in incorporating the filtration distance. An algorithm is presented for selecting and removing nodes of a scenario tree such that a prescribed error tolerance is met. Some numerical experience is reported.
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