416 search results - page 2 / 84 » Approximation Algorithms for Reliable Stochastic Combinatori... |
DAGSTUHL
2007
13 years 6 months ago
2007
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
EMO
2009
Springer
13 years 11 months ago
2009
Springer
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision...
FOCS
2005
IEEE
13 years 10 months ago
2005
IEEE
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
SAGA
2005
Springer
13 years 10 months ago
2005
Springer
Two general-purpose metaheuristic algorithms for solving multiobjective stochastic combinatorial optimization problems are introduced: SP-ACO (based on the Ant Colony Optimization ...
IPCO
2007
13 years 6 months ago
2007
Following the well-studied two-stage optimization framework for stochastic optimization [15, 18], we study approximation algorithms for robust two-stage optimization problems with ...