This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
We consider the total weighted completion time scheduling problem for parallel identical machines and precedence constraints, P jprecj PwiCi. This important and broad class of pro...
Ivan D. Baev, Waleed Meleis, Alexandre E. Eichenbe...
We describe a simple on-line heuristic for scheduling job-shops. We assume there is a fixed set of routes for the jobs, and many jobs, say N, on each route. The heuristic uses saf...