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FOCS
2005
IEEE
14 years 2 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
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...
Chaitanya Swamy, David B. Shmoys
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
14 years 2 months ago
A GA for maximum likelihood phylogenetic inference using neighbour-joining as a genotype to phenotype mapping
Evolutionary relationships among species can be represented by a phylogenetic tree and inferred by optimising some measure of fitness, such as the statistical likelihood of the t...
Leon Poladian
GECCO
2007
Springer
150views Optimization» more  GECCO 2007»
14 years 2 months ago
Credit assignment in adaptive memetic algorithms
Adaptive Memetic Algorithms couple an evolutionary algorithm with a number of local search heuristics for improving the evolving solutions. They are part of a broad family of meta...
J. E. Smith
SODA
2010
ACM
175views Algorithms» more  SODA 2010»
14 years 6 months ago
Fast SDP Algorithms for Constraint Satisfaction Problems
The class of constraint satisfactions problems (CSPs) captures many fundamental combinatorial optimization problems such as Max Cut, Max q-Cut, Unique Games, and Max k-Sat. Recent...
David Steurer
EUROCAST
2007
Springer
132views Hardware» more  EUROCAST 2007»
14 years 14 days ago
Using Omnidirectional BTS and Different Evolutionary Approaches to Solve the RND Problem
RND (Radio Network Design) is an important problem in mobile telecommunications (for example in mobile/cellular telephony), being also relevant in the rising area of sensor network...
Miguel A. Vega-Rodríguez, Juan Antonio G&oa...