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» On Benchmarking Stochastic Global Optimization Algorithms
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SARA
2007
Springer
14 years 1 months ago
Approximate Model-Based Diagnosis Using Greedy Stochastic Search
Most algorithms for computing diagnoses within a modelbased diagnosis framework are deterministic. Such algorithms guarantee soundness and completeness, but are NPhard. To overcom...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
CEC
2008
IEEE
13 years 8 months ago
A technique for the visualization of population-based algorithms
— A technique for the visualization of stochastic population–based algorithms in multidimensional problems with known global minimizers is proposed. The technique employs proje...
Konstantinos E. Parsopoulos, Voula C. Georgopoulos...
ICDCS
2010
IEEE
13 years 11 months ago
Stochastic Steepest-Descent Optimization of Multiple-Objective Mobile Sensor Coverage
—We propose a steepest descent method to compute optimal control parameters for balancing between multiple performance objectives in stateless stochastic scheduling, wherein the ...
Chris Y. T. Ma, David K. Y. Yau, Nung Kwan Yip, Na...
ISLPED
2010
ACM
183views Hardware» more  ISLPED 2010»
13 years 8 months ago
A pareto-algebraic framework for signal power optimization in global routing
This paper proposes a framework for (signal) interconnect power optimization at the global routing stage. In a typical design flow, the primary objective of global routing is mini...
Hamid Shojaei, Tai-Hsuan Wu, Azadeh Davoodi, Twan ...
CDC
2008
IEEE
130views Control Systems» more  CDC 2008»
14 years 2 months ago
Stochastic multiscale approaches to consensus problems
Abstract— While peer-to-peer consensus algorithms have enviable robustness and locality for distributed estimation and computation problems, they have poor scaling behavior with ...
Jong-Han Kim, Matthew West, Sanjay Lall, Eelco Sch...