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Solving Multi-Stage Stochastic Capacity-Planning Problems


Speaker: Prof. Andy Philpott, University of Auckland
Location: 2112 MSB
Start time: Fri, Jan 20 2006, 2:10PM

We describe a general multi-stage stochastic integer-programming model for planning the discrete capacity expansion of production facilities in a situation in which a scenario tree represents uncertainty. A split-variable reformulation of the basic model leads to a strong Dantzig-Wolfe decomposition, whose efficiency we demonstrate on a capacity-expansion model for electric power distribution. When a facility can expand at most once over the planning horizon, a specialised model yields substantial computational savings. (Joint work with Kavinesh Singh and Kevin Wood)