Title :
A review of machine learning in scheduling
Author :
Aytug, Haldun ; Bhattacharyya, Siddhartha ; Koehler, Gary J. ; Snowdon, Jane L.
Author_Institution :
Dept. of Decision & Inf. Sci., Florida Univ., Gainesville, FL, USA
fDate :
5/1/1994 12:00:00 AM
Abstract :
This paper has two primary purposes: to motivate the need for machine learning in scheduling systems and to survey work on machine learning in scheduling. In order to motivate the need for machine learning in scheduling, we briefly motivate the need for systems employing artificial intelligence methods for scheduling. This leads to a need for incorporating adaptive methods-learning
Keywords :
learning (artificial intelligence); reviews; scheduling; adaptive methods; artificial intelligence methods; machine learning; scheduling; Artificial intelligence; Dynamic scheduling; Environmental management; Job shop scheduling; Machine learning; Manufacturing processes; Parallel processing; Processor scheduling; Production planning; Uncertainty;
Journal_Title :
Engineering Management, IEEE Transactions on
