Generating University Course Timetable Using Genetic Algorithms and Local Search

In this paper we establish a new algorithm based on genetic algorithms (GA) and sequential local search to solve course timetabling problem. Universities are challenged to arise in number of complexity, their resources and events are becoming harder to schedule. Timetabling is a kind of problem in which events (classes, exams, courses, etc) have to be arranged into a number of timeslots such that conflicts in using a given set of resources are avoided. We perform preliminary experiments on standard benchmark course timetable problems and able to produce promising results.

[1]  Luca Di Gaspero,et al.  Tabu Search Techniques for Examination Timetabling , 2000, PATAT.

[2]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[3]  A. Hertz.  Tabu search for large scale timetabling problems , 1991 .

[4]  Peter J. Fleming,et al.  GENETIC ALGORITHMS IN CONTROL SYSTEMS ENGINEERING , 2001 .

[5]  P. Adamidis,et al.  Evolutionary algorithms in lecture timetabling , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[6]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1992, Artificial Intelligence.

[7]  Michael W. Carter,et al.  OR Practice - A Survey of Practical Applications of Examination Timetabling Algorithms , 1986, Oper. Res..

[8]  Guy Albert Dumont,et al.  System identification and control using genetic algorithms , 1992, IEEE Trans. Syst. Man Cybern..

[9]  Edmund K. Burke,et al.  Using a Randomised Iterative Improvement Algorithm with Composite Neighbourhood Structures for the University Course Timetabling Problem , 2007, Metaheuristics.

[10]  E. Burke,et al.  A Randomised Iterative Improvement Algorithm with Composite Neighbourhood Structures for University Course Timetabling , 2005 .

[11]  Marco Dorigo,et al.  Genetic Algorithms: A New Approach to the Timetable Problem , 1992 .

[12]  Marco Dorigo,et al.  Metaheuristics for High School Timetabling , 1998, Comput. Optim. Appl..

[13]  Pupong Pongcharoen,et al.  The development of genetic algorithms for the finite capacity scheduling of complex products, with multiple levels of product structure , 2004, Eur. J. Oper. Res..

[14]  Edmund K. Burke,et al.  A multistage evolutionary algorithm for the timetable problem , 1999, IEEE Trans. Evol. Comput..

[15]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[16]  Arabinda Tripathy.  A Lagrangean Relaxation Approach to Course Timetabling , 1980 .

[17]  E. Burke,et al.  AN INVESTIGATION OF VARIABLE NEIGHBOURHOOD SEARCH FOR UNIVERSITY COURSE TIMETABLING , 2005 .

[18]  Kay Chen Tan,et al.  Solving the Exam Timetabling Problem via a Multi-Objective Evolutionary Algorithm - A More General Approach , 2007, 2007 IEEE Symposium on Computational Intelligence in Scheduling.

[19]  David Abramson,et al.  Constructing school timetables using simulated annealing: sequential and parallel algorithms , 1991 .

[20]  P. Pongcharoena,et al.  Determining optimum Genetic Algorithm parameters for scheduling the manufacturing and assembly of complex products , 2002 .

[21]  E. Burke,et al.  A New Adaptive Heuristic Framework for Examination Timetabling Problems , 2002 .

[22]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[23]  Agostinho C. Rosa,et al.  School Timetabling using Genetic Search , 1997 .

[24]  Mauro Birattari,et al.  An effective hybrid approach for the university course timetabling problem , 2003 .

[25]  Chris N. Potts,et al.  Constraint satisfaction problems: Algorithms and applications , 1999, Eur. J. Oper. Res..

[26]  J. Grefenstette,et al.  EVOLVING ROBOT BEHAVIORS , 1994 .

[27]  Gilbert Laporte,et al.  Recent Developments in Practical Course Timetabling , 1997, PATAT.

[28]  Omar el Mahdi,et al.  Using a genetic algorithm optimizer tool to generate good quality timetables , 2003, 10th IEEE International Conference on Electronics, Circuits and Systems, 2003. ICECS 2003. Proceedings of the 2003.

[29]  Ben Paechter,et al.  Extensions to a Memetic Timetabling System , 1995, PATAT.

[30]  Andrea Schaerf,et al.  A Survey of Automated Timetabling , 1999, Artificial Intelligence Review.