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IJCAI
2001
15 years 1 months ago
Backbones in Optimization and Approximation
We study the impact of backbones in optimization and approximation problems. We show that some optimization problems like graph coloring resemble decision problems, with problem h...
John K. Slaney, Toby Walsh
IPCO
1998
152views Optimization» more  IPCO 1998»
15 years 1 months ago
Approximation Bounds for a General Class of Precedence Constrained Parallel Machine Scheduling Problems
Abstract. A well studied and difficult class of scheduling problems concerns parallel machines and precedence constraints. In order to model more realistic situations, we consider ...
Alix Munier, Maurice Queyranne, Andreas S. Schulz
IOR
2007
58views more  IOR 2007»
14 years 11 months ago
Bounds, Heuristics, and Approximations for Distribution Systems
This paper develops simple approximate methods to analyze a two-stage stochastic distribution system consisting of one warehouse and multiple retailers. We consider local and cent...
Guillermo Gallego, Özalp Özer, Paul H. Z...
SIAMJO
2002
124views more  SIAMJO 2002»
14 years 11 months ago
The Sample Average Approximation Method for Stochastic Discrete Optimization
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
Anton J. Kleywegt, Alexander Shapiro, Tito Homem-d...
ICML
2008
IEEE
16 years 21 days ago
Democratic approximation of lexicographic preference models
Previous algorithms for learning lexicographic preference models (LPMs) produce a "best guess" LPM that is consistent with the observations. Our approach is more democra...
Fusun Yaman, Thomas J. Walsh, Michael L. Littman, ...