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- W2949148001 abstract "We consider a class of multi-stage robust covering problems, where additional information is revealed about the problem instance in each stage, but the cost of taking actions increases. The dilemma for the decision-maker is whether to wait for additional information and risk the inflation, or to take early actions to hedge against rising costs. We study the uncertainty model: in each stage i = 0, 1,...,T, the algorithm is shown some subset of size k_i that completely contains the eventual demands to be covered; here k_1 > k_2 >...> k_T which ensures increasing information over time. The goal is to minimize the cost incurred in the worst-case possible sequence of revelations. For the multistage k-robust set cover problem, we give an O(log m + log n)-approximation algorithm, nearly matching the Omega(log n + log m/loglog m) hardness of approximation even for T=2 stages. Moreover, our algorithm has a useful property: it takes actions on just two stages. We show similar thrifty algorithms for multi-stage k-robust Steiner tree, Steiner forest, and minimum-cut. For these problems our approximation guarantees are O(min{T, log n, log L_{max}), where L_{max} is the maximum inflation over all the stages. We conjecture that these problems also admit O(1)-approximate thrifty algorithms." @default.
- W2949148001 created "2019-06-27" @default.
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- W2949148001 date "2013-02-21" @default.
- W2949148001 modified "2023-09-27" @default.
- W2949148001 title "Thrifty Algorithms for Multistage Robust Optimization" @default.
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