Abstract
Class scheduling is a complex combinatorial optimization problem which involves determining the most desirable schedule of lecture times and classes for each teacher under the constraints as to instructors, students, and facilities. In this paper, a class scheduling system by neurocomputing using the calicula at Hannan University as a model is presented. A quantitative comparison of the system with the previously developed rule-based system is made. It is shown that the neurocomputing-based approach is superior to the rule-based approach, especially in the case that several conflicting evaluation conditions are interwoven like the class scheduling in this study.
