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APPROX
2010
Springer
188views Algorithms» more  APPROX 2010»
13 years 9 months ago
Approximation Algorithms for Reliable Stochastic Combinatorial Optimization
We consider optimization problems that can be formulated as minimizing the cost of a feasible solution wT x over an arbitrary combinatorial feasible set F {0, 1}n . For these pro...
Evdokia Nikolova
SIGECOM
2004
ACM
96views ECommerce» more  SIGECOM 2004»
14 years 25 days ago
A stochastic programming approach to scheduling in TAC SCM
In this paper, we combine two approaches to handling uncertainty: we use techniques for finding optimal solutions in the expected sense to solve combinatorial optimization proble...
Michael Benisch, Amy R. Greenwald, Victor Narodits...
AAAI
2011
12 years 7 months ago
Linear Dynamic Programs for Resource Management
Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...
Marek Petrik, Shlomo Zilberstein
AIPS
2004
13 years 8 months ago
Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
Branislav Kveton, Milos Hauskrecht
CCE
2008
13 years 7 months ago
Chance constrained programming approach to process optimization under uncertainty
Deterministic optimization approaches have been well developed and widely used in the process industry to accomplish off-line and on-line process optimization. The challenging tas...
Pu Li, Harvey Arellano-Garcia, Günter Wozny