An artificial intelligence approach to course timetabling

Lien-Fu Lai, Chao-Chin Wu, Nien Lin Hsueh, Liang Tsung Huang, Shiow Fen Hwang

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Course Timetabling is a complex problem that cannot be dealt with by using only a few general principles. The various actors (the administrator, the chairman, the instructor and the student) have their own objectives, and these objectives usually conflict. The complexity of the relationships among time slots, classes, classrooms, and instructors makes it difficult to achieve a feasible solution. In this article, we propose an artificial intelligence approach that integrates expert systems and constraint programming to implement a course timetabling system. Expert systems are utilized to incorporate knowledge into the timetabling system and to provide a reasoning capability for knowledge deduction. Separating out the knowledge base, the facts, and the inference engine in expert systems provides greater flexibility in supporting changes. The constraint hierarchy and the constraint network are utilized to capture hard and soft constraints and to reason about constraints by using constraint satisfaction and relaxation techniques. In addition, object-oriented software engineering is applied to improve the development and maintenance of the course timetabling system. A course timetabling system in the Department of Computer Science and Information Engineering at the National Changhua University of Education (NCUE) is used as an illustrative example of the proposed approach.

Original languageEnglish
Pages (from-to)223-240
Number of pages18
JournalInternational Journal on Artificial Intelligence Tools
Volume17
Issue number1
DOIs
Publication statusPublished - 2008 Feb 1

Fingerprint

Expert systems
Artificial intelligence
Inference engines
Computer science
Software engineering
Education
Students

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Lai, Lien-Fu ; Wu, Chao-Chin ; Hsueh, Nien Lin ; Huang, Liang Tsung ; Hwang, Shiow Fen. / An artificial intelligence approach to course timetabling. In: International Journal on Artificial Intelligence Tools. 2008 ; Vol. 17, No. 1. pp. 223-240.
@article{8e521cf063894c009d9d3c5351fc71d2,
title = "An artificial intelligence approach to course timetabling",
abstract = "Course Timetabling is a complex problem that cannot be dealt with by using only a few general principles. The various actors (the administrator, the chairman, the instructor and the student) have their own objectives, and these objectives usually conflict. The complexity of the relationships among time slots, classes, classrooms, and instructors makes it difficult to achieve a feasible solution. In this article, we propose an artificial intelligence approach that integrates expert systems and constraint programming to implement a course timetabling system. Expert systems are utilized to incorporate knowledge into the timetabling system and to provide a reasoning capability for knowledge deduction. Separating out the knowledge base, the facts, and the inference engine in expert systems provides greater flexibility in supporting changes. The constraint hierarchy and the constraint network are utilized to capture hard and soft constraints and to reason about constraints by using constraint satisfaction and relaxation techniques. In addition, object-oriented software engineering is applied to improve the development and maintenance of the course timetabling system. A course timetabling system in the Department of Computer Science and Information Engineering at the National Changhua University of Education (NCUE) is used as an illustrative example of the proposed approach.",
author = "Lien-Fu Lai and Chao-Chin Wu and Hsueh, {Nien Lin} and Huang, {Liang Tsung} and Hwang, {Shiow Fen}",
year = "2008",
month = "2",
day = "1",
doi = "10.1142/S0218213008003868",
language = "English",
volume = "17",
pages = "223--240",
journal = "International Journal on Artificial Intelligence Tools",
issn = "0218-2130",
publisher = "World Scientific Publishing Co. Pte Ltd",
number = "1",

}

An artificial intelligence approach to course timetabling. / Lai, Lien-Fu; Wu, Chao-Chin; Hsueh, Nien Lin; Huang, Liang Tsung; Hwang, Shiow Fen.

In: International Journal on Artificial Intelligence Tools, Vol. 17, No. 1, 01.02.2008, p. 223-240.

Research output: Contribution to journalArticle

TY - JOUR

T1 - An artificial intelligence approach to course timetabling

AU - Lai, Lien-Fu

AU - Wu, Chao-Chin

AU - Hsueh, Nien Lin

AU - Huang, Liang Tsung

AU - Hwang, Shiow Fen

PY - 2008/2/1

Y1 - 2008/2/1

N2 - Course Timetabling is a complex problem that cannot be dealt with by using only a few general principles. The various actors (the administrator, the chairman, the instructor and the student) have their own objectives, and these objectives usually conflict. The complexity of the relationships among time slots, classes, classrooms, and instructors makes it difficult to achieve a feasible solution. In this article, we propose an artificial intelligence approach that integrates expert systems and constraint programming to implement a course timetabling system. Expert systems are utilized to incorporate knowledge into the timetabling system and to provide a reasoning capability for knowledge deduction. Separating out the knowledge base, the facts, and the inference engine in expert systems provides greater flexibility in supporting changes. The constraint hierarchy and the constraint network are utilized to capture hard and soft constraints and to reason about constraints by using constraint satisfaction and relaxation techniques. In addition, object-oriented software engineering is applied to improve the development and maintenance of the course timetabling system. A course timetabling system in the Department of Computer Science and Information Engineering at the National Changhua University of Education (NCUE) is used as an illustrative example of the proposed approach.

AB - Course Timetabling is a complex problem that cannot be dealt with by using only a few general principles. The various actors (the administrator, the chairman, the instructor and the student) have their own objectives, and these objectives usually conflict. The complexity of the relationships among time slots, classes, classrooms, and instructors makes it difficult to achieve a feasible solution. In this article, we propose an artificial intelligence approach that integrates expert systems and constraint programming to implement a course timetabling system. Expert systems are utilized to incorporate knowledge into the timetabling system and to provide a reasoning capability for knowledge deduction. Separating out the knowledge base, the facts, and the inference engine in expert systems provides greater flexibility in supporting changes. The constraint hierarchy and the constraint network are utilized to capture hard and soft constraints and to reason about constraints by using constraint satisfaction and relaxation techniques. In addition, object-oriented software engineering is applied to improve the development and maintenance of the course timetabling system. A course timetabling system in the Department of Computer Science and Information Engineering at the National Changhua University of Education (NCUE) is used as an illustrative example of the proposed approach.

UR - http://www.scopus.com/inward/record.url?scp=43949102057&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=43949102057&partnerID=8YFLogxK

U2 - 10.1142/S0218213008003868

DO - 10.1142/S0218213008003868

M3 - Article

AN - SCOPUS:43949102057

VL - 17

SP - 223

EP - 240

JO - International Journal on Artificial Intelligence Tools

JF - International Journal on Artificial Intelligence Tools

SN - 0218-2130

IS - 1

ER -