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» Sequential sampling for solving stochastic programs
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GECCO
2010
Springer
237views Optimization» more  GECCO 2010»
13 years 10 months ago
Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noiseless BBOB-2010 testbed
The well-known Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a robust stochastic search algorithm for optimizing functions defined on a continuous search space RD ....
Anne Auger, Dimo Brockhoff, Nikolaus Hansen
MP
2006
103views more  MP 2006»
13 years 5 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
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
13 years 11 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
ISQED
2010
IEEE
123views Hardware» more  ISQED 2010»
13 years 7 months ago
Yield-constrained digital circuit sizing via sequential geometric programming
Circuit design under process variation can be formulated mathematically as a robust optimization problem with a yield constraint. Existing methods force designers to either resort...
Yu Ben, Laurent El Ghaoui, Kameshwar Poolla, Costa...
RSS
2007
136views Robotics» more  RSS 2007»
13 years 7 months ago
The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
Ron Alterovitz, Thierry Siméon, Kenneth Y. ...