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...
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...
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...
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...
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...