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» A branch and bound method for stochastic global optimization
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SAGA
2009
Springer
15 years 4 months ago
Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies
We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible dec...
Boris Defourny, Damien Ernst, Louis Wehenkel
DGCI
2008
Springer
14 years 11 months ago
Robust Estimation of Curvature along Digital Contours with Global Optimization
In this paper we introduce a new curvature estimator based on global optimisation. This method called Global Min-Curvature exploits the geometric properties of digital contours by ...
Bertrand Kerautret, Jacques-Olivier Lachaud
78
Voted
MP
2006
103views more  MP 2006»
14 years 9 months ago
Assessing solution quality in stochastic programs
Determining if a solution is optimal or near optimal is fundamental in optimization theory, algorithms, and computation. For instance, Karush-Kuhn-Tucker conditions provide necessa...
Güzin Bayraksan, David P. Morton
85
Voted
HEURISTICS
2006
197views more  HEURISTICS 2006»
14 years 9 months ago
Bucket elimination for multiobjective optimization problems
Multiobjective optimization deals with problems involving multiple measures of performance that should be optimized simultaneously. In this paper we extend bucket elimination (BE),...
Emma Rollon, Javier Larrosa
95
Voted
CDC
2009
IEEE
285views Control Systems» more  CDC 2009»
14 years 7 months ago
Adaptive randomized algorithm for finding eigenvector of stochastic matrix with application to PageRank
Abstract-- The problem of finding the eigenvector corresponding to the largest eigenvalue of a stochastic matrix has numerous applications in ranking search results, multi-agent co...
Alexander V. Nazin, Boris T. Polyak