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LATIN
2000
Springer
14 years 9 days ago
Approximation Algorithms for Flexible Job Shop Problems
The Flexible Job Shop problem is a generalization of the classical job shop scheduling problem in which for every operation there is a group of machines that can process it. The p...
Klaus Jansen, Monaldo Mastrolilli, Roberto Solis-O...
BMCBI
2008
142views more  BMCBI 2008»
13 years 8 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
EOR
2010
104views more  EOR 2010»
13 years 6 months ago
New solution methods for single machine bicriteria scheduling problem: Minimization of average flowtime and number of tardy jobs
We consider the bicriteria scheduling problem of minimizing the number of tardy jobs and average flowtime on a single machine. This problem, which is known to be NP-hard, is impor...
Fatih Safa Erenay, Ihsan Sabuncuoglu, Aysegül...
CISS
2008
IEEE
14 years 3 months ago
Imperfect randomized algorithms for the optimal control of wireless networks
Abstract— We consider a joint randomized scheduling, congestion control mechanism for general wireless networks. We allow for a set of imperfections in the operation of the rando...
Atilla Eryilmaz, Asuman E. Ozdaglar, Devavrat Shah...
ITRE
2005
IEEE
14 years 2 months ago
Structure learning of Bayesian networks using a semantic genetic algorithm-based approach
A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qual...
Sachin Shetty, Min Song