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ORL
2010
108views more  ORL 2010»
12 years 11 months ago
Easy distributions for combinatorial optimization problems with probabilistic constraints
We show how we can linearize probabilistic linear constraints with binary variables when all coefficients are distributed according to either N(
Bernard Fortz, Michael Poss
FOCS
2004
IEEE
13 years 8 months ago
Stochastic Optimization is (Almost) as easy as Deterministic Optimization
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
David B. Shmoys, Chaitanya Swamy
IJCAI
2001
13 years 6 months ago
CABOB: A Fast Optimal Algorithm for Combinatorial Auctions
Combinatorial auctions where bidders can bid on bundles of items can lead to more economical allocations, but determining the winners is NP-complete and inapproximable. We present...
Tuomas Sandholm, Subhash Suri, Andrew Gilpin, Davi...
AAAI
2006
13 years 6 months ago
A New Approach to Distributed Task Assignment using Lagrangian Decomposition and Distributed Constraint Satisfaction
We present a new formulation of distributed task assignment, called Generalized Mutual Assignment Problem (GMAP), which is derived from an NP-hard combinatorial optimization probl...
Katsutoshi Hirayama
STOC
2004
ACM
150views Algorithms» more  STOC 2004»
14 years 5 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking