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113
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AIPS
1994
15 years 5 months ago
Solving Time-critical Decision-making Problems with Predictable Computational Demands
In this work we present an approach to solving time-critical decision-making problems by taking advantage of domain structure to expand the amountof time available for processing ...
Thomas Dean, Lloyd Greenwald
135
Voted
EMO
2009
Springer
174views Optimization» more  EMO 2009»
15 years 10 months ago
Constraint Programming
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision...
Pascal Van Hentenryck
119
Voted
AAAI
2000
15 years 5 months ago
Solving Combinatorial Auctions Using Stochastic Local Search
Combinatorial auctions (CAs) have emerged as an important model in economics and show promise as a useful tool for tackling resource allocation in AI. Unfortunately, winner determ...
Holger H. Hoos, Craig Boutilier
159
Voted
IPCO
2004
144views Optimization» more  IPCO 2004»
15 years 5 months ago
Hedging Uncertainty: Approximation Algorithms for Stochastic Optimization Problems
Abstract. We study two-stage, finite-scenario stochastic versions of several combinatorial optimization problems, and provide nearly tight approximation algorithms for them. Our pr...
R. Ravi, Amitabh Sinha
147
Voted
SAGA
2009
Springer
15 years 10 months ago
Scenario Reduction Techniques in Stochastic Programming
Stochastic programming problems appear as mathematical models for optimization problems under stochastic uncertainty. Most computational approaches for solving such models are base...
Werner Römisch