416 search results - page 5 / 84 » Approximation Algorithms for Reliable Stochastic Combinatori... |
ANTSW
2010
Springer
13 years 3 months ago
2010
Springer
Abstract. Ant algorithms are usually derived from a stochastic modeling based on some specific probability laws. We consider in this paper a full deterministic model of "logis...
FSTTCS
2006
Springer
14 years 7 days ago
2006
Springer
Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
MOR
2007
13 years 8 months ago
2007
Real-world networks often need to be designed under uncertainty, with only partial information and predictions of demand available at the outset of the design process. The field ...
SAGA
2009
Springer
14 years 3 months ago
2009
Springer
Stochastic programming problems appear as mathematical models for optimization problems under stochastic uncertainty. Most computational approaches for solving such models are base...
APPROX
2008
Springer
13 years 10 months ago
2008
Springer
Abstract. In this paper, we propose a general framework for designing fully polynomial time approximation schemes for combinatorial optimization problems, in which more than one ob...