Mittagsseminar (in cooperation with A. Steger, D. Steurer and B. Sudakov)

Date and Time: Thursday, December 22, 2005, 12:15 pm

Duration: This information is not available in the database

Location: This information is not available in the database

Speaker: Florian Walpen

Boosted Sampling: Approximation Algorithms for Stochastic Optimization

Several combinatorial optimization problems choose elements to minimize the total cost of constructing a feasible solution that satisfies requirements of clients. In the Steiner Tree problem, for example, edges must be chosen to connect terminals (clients). The authors consider a stochastic version of such a problem where the solution is constructed in two stages: Before the actual requirements materialize, we can choose elements in a first stage. The actual requirements are then revealed, drawn from a pre-specified probability distribution F thereupon, some more elements may be chosen to obtain a feasible solution for the actual requirements. However, in this second (recourse) stage, choosing an element is costlier by a factor of s > 1. The goal is to minimize the first stage cost plus the expected second stage cost.

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