Electromagnetism-like Mechanism with Force Decay Rate Great Deluge for the Course Timetabling Problem

Combinations of population-based approaches with local search have provided very good results for a variety of scheduling problems. This paper describes the development of a population-based algorithm called Electromagnetism-like mechanism with force decay rate great deluge algorithm for university course timetabling. This problem is concerned with the assignment of lectures to a specific numbers of timeslots and rooms. For a solution to be feasible, a number of hard constraints must be satisfied. A penalty value which represents the degree to which various soft constraints are satisfied is measured which reflects the quality of the solution. This approach is tested over established datasets and compared against state-of-the-art techniques from the literature. The results obtained confirm that the approach is able to produce solutions to the course timetabling problem which demonstrate some of the lowest penalty values in the literature on these benchmark problems.

[1]  Graham Kendall,et al.  A Tabu-Search Hyperheuristic for Timetabling and Rostering , 2003, J. Heuristics.

[2]  S. Abdullah,et al.  Generating University Course Timetable Using Genetic Algorithms and Local Search , 2008, 2008 Third International Conference on Convergence and Hybrid Information Technology.

[3]  Mario Vanhoucke,et al.  An electromagnetic meta-heuristic for the nurse scheduling problem , 2007, J. Heuristics.

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

[5]  Michael Sampels,et al.  A MAX-MIN Ant System for the University Course Timetabling Problem , 2002, Ant Algorithms.

[6]  Sanja Petrovic,et al.  A graph-based hyper-heuristic for educational timetabling problems , 2007, Eur. J. Oper. Res..

[7]  Edmund K. Burke,et al.  Analyzing the landscape of a graph based hyper-heuristic for timetabling problems , 2009, GECCO.

[8]  Ben Paechter,et al.  Setting the Research Agenda in Automated Timetabling: The Second International Timetabling Competition , 2010, INFORMS J. Comput..

[9]  G. Dueck.  New optimization heuristics , 1993 .

[10]  Mario Vanhoucke,et al.  An electromagnetism meta-heuristic for project scheduling , 2004 .

[11]  Edmund K. Burke,et al.  A Multi-Start Very Large Neighbourhood Search Approach with Local Search Methods for Examination Timetabling , 2006, ICAPS.

[12]  Ben Paechter,et al.  A Comparison of the Performance of Different Metaheuristics on the Timetabling Problem , 2002, PATAT.

[13]  Paul McMullan,et al.  An Extended Implementation of the Great Deluge Algorithm for Course Timetabling , 2007, International Conference on Computational Science.

[14]  Mario Vanhoucke,et al.  AN ELECTROMAGNETISM META-HEURISTIC FOR THE RESOURCE-CONSTRAINED PROJECT SCHEDULING PROBLEM , 2004 .

[15]  Mario Vanhoucke,et al.  The Electromagnetism Meta-heuristic Applied to the Resource-Constrained Project Scheduling Problem , 2005, Artificial Evolution.

[16]  Shu-Cherng Fang,et al.  On the Convergence of a Population-Based Global Optimization Algorithm , 2004, J. Glob. Optim..

[17]  Shu-Cherng Fang,et al.  An Electromagnetism-like Mechanism for Global Optimization , 2003, J. Glob. Optim..

[18]  Michel Gendreau,et al.  Metaheuristics: Progress in Complex Systems Optimization , 2007 .

[19]  Edmund K. Burke,et al.  A hybrid evolutionary approach to the university course timetabling problem , 2007, 2007 IEEE Congress on Evolutionary Computation.

[20]  Joseph Y.-T. Leung,et al.  Handbook of Scheduling: Algorithms, Models, and Performance Analysis , 2004 .

[21]  Sanja Petrovic,et al.  University Timetabling , 2004, Handbook of Scheduling.

[22]  Edmund K. Burke,et al.  Practice and Theory of Automated Timetabling VI, 6th International Conference, PATAT 2006, Brno, Czech Republic, August 30 - September 1, 2006, Revised Selected Papers , 2007, PATAT.

[23]  Bert De Reyck,et al.  A hybrid scatter search/electromagnetism meta-heuristic for project scheduling , 2006, Eur. J. Oper. Res..

[24]  Jack Dongarra,et al.  Computational Science - ICCS 2007, 7th International Conference, Beijing, China, May 27 - 30, 2007, Proceedings, Part III , 2007, ICCS.

[25]  Barry McCollum,et al.  A Perspective on Bridging the Gap Between Theory and Practice in University Timetabling , 2006, PATAT.

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

[27]  Luiz Satoru Ochi,et al.  New heuristics for the maximum diversity problem , 2007, J. Heuristics.

[28]  Edmund K. Burke,et al.  Practice and Theory of Automated Timetabling IV , 2002, Lecture Notes in Computer Science.

[29]  D. Landa-Silva,et al.  Great deluge with non-linear decay rate for solving course timetabling problems , 2008, 2008 4th International IEEE Conference Intelligent Systems.

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