Solving university course timetabling problems using constriction particle swarm optimization with local search

Algorithms

Volumn 6, Issue 2, 2013, Pages 227-244

  Chen, Ruey Maw ^a   Shih, Hsiao Fang ^a  

^a NATIONAL CHIN YI UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

Constriction factor; Course timetabling; Interchange; Particle swarm optimization; Soft constraint

Indexed keywords

COMBINATORIAL OPTIMIZATION PROBLEMS; CONSTRICTION FACTOR; COURSE TIMETABLING; ENVIRONMENTAL CHARACTERISTIC; FAST CONVERGENCE; PARAMETER SETTING; SOFT CONSTRAINT; UNIVERSITY COURSE TIMETABLING-PROBLEMS;

COMPUTATIONAL COMPLEXITY; CONSTRAINT THEORY; CURRICULA; INTERCHANGES; PARTICLE SWARM OPTIMIZATION (PSO); PETROLEUM REFINING; SCHEDULING; SURVEYS; TEACHING;

PROBLEM SOLVING;

EID: 84880411060     PISSN: None     EISSN: 19994893     Source Type: Journal    
DOI: 10.3390/a6020227     Document Type: Article

References (27)

1. Mooney, E.L.; Rardin, R.L.; Parmenter, W.J. Large scale classroom scheduling. IIE Trans. 1995, 28, 369-378.
2. Even, S.; Itai, A.; Shamir, A. On the Complexity of Timetable and Multi-Commodity Flow Problems. In Proceedings of the 16th IEEE Annual Symposium on Foundations of Computer Science, California, CA, USA, 13-15 October 1975; pp. 184-193.
3. Herz, A. Tabu search for large scale timetabling problems. Eur. J. Oper. Res. 1991, 54, 39-47.
4. Masood, A.B. A two-stage multiobjective scheduling model for faculty-course-time assignment. Eur. J. Oper. Res. 1996, 94, 16-28.
5. Werra, D. Restricted coloring models for timetabling. Discret. Math. 1997, 165-166, 161-170.
6. Abdullah, S.; Turabieh, H. Generating university course timetable using genetic algorithm and local search. In Proceedings of the 3rd International Conference on Convergence and Hybrid Information Technology, Busan, Korea, 11-13 November 2008; pp. 254-260.
7. Cambazard, H.; Hebrard, E.; O'Sullivan, B.; Papadopoulos, A. Local search and constraint programming for the post enrolment-based course timetabling problem. Ann. Oper. Res. 2012, 194, 111-135.
8. Gunawan, A.; Ng, K.M.; Poh, K.L. A hybridized Lagrangian relaxation and simulated annealing method for the course timetabling problem. Comput. Oper. Res. 2012, 39, 3074-3088.
9. Burke, E.K.; Elliman, D.G.; Weare, R.F. Application of genetic algorithm for solving university timetabling problems: A case study of Thai universities. In Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization, Beijing, China, 15-17 September, 2007; pp. 128-133.
10. Nothegger, C.; Mayer, A.; Chwatal, A.; Raidl, G. Solving the post enrolment course timetabling problem by ant colony optimisation. Ann. Oper. Res. 2012, 194, 325-339.
11. Shiau, D.F. A hybrid particle swarm optimization for a university course scheduling problem with flexible preferences. Expert Syst. Appl. 2011, 38, 235-248.
12. Tassopoulos, I.X.; Beligiannis, G.N. A hybrid particle swarm optimization based algorithm for high school timetabling problems. Appl. Soft Comput. 2012, 12, 3472-3489.
13. Al-Betar, M.A.; Khader, A.T.; Zaman, M. University course timetabling using a hybrid harmony search metaheuristic algorithm. IEEE Trans. Syst. Man Cybern. Rev. 2012, 42, 664-681.
14. Jat, S.; Yang, S. A hybrid genetic algorithm and tabu search approach for post enrolment course timetabling. J. Sched. 2010, 14, 617-637.
15. Kennedy, J.; Eberhart, R. Particle Swarm Optimization. In Proceedings of the Fourth IEEE International Conference on Neural Networks, Perth, WA, USA, 27 November-1 December 1995; pp. 1942-1948.
16. Marinakis, Y.; Marinaki, M. A hybrid multi-swarm particle swarm optimization algorithm for the probabilistic traveling salesman problem. Comput. Oper. Res. 2010, 37, 432-442.
17. Liu, B.; Wang, L.; Jin, Y.H. An Effective PSO-Based Memetic Algorithm for Flow Shop Scheduling. IEEE Trans. Syst. Man Cybern. Rev. 2007, 37, 18-27.
18. Shen, H.; Zhu, Y.; Liu, T.; Jin, L. Particle Swarm Optimization in Solving Vehicle Routing Problem. ICICTA 09' Second International Conference on Intelligent Computation Technology and Automation, Hunan, China, 10-11 October 2009; pp. 287-291.
19. Chen, R.M.; Wang, C.M. Project scheduling heuristics based standard PSO for task-resource assignment in heterogeneous grid. Abstr. Appl. Anal. 2011, 2011, doi:10.1155/2011/589862.
20. Chen, R.M.; Wu, C.L.; Wang, C.M.; Lo, S.T. Using a novel particle swarm optimization scheme to solve resource-constrained scheduling problem in PSPLIB. Expert Syst. Appl. 2010, 37, 1899-1910.
21. Chen, R.M. Particle swarm optimization with justification and designed mechanisms for resource-constrained project scheduling problem. Expert Syst. Appl. 2011, 38, 7102-7111.
22. Shi, Y.; Eberhart, R. A Modified Particle Swarm Optimizer. In Proceedings of the IEEE International Conference on Evolutionary Computation, Anchorage, Piscataway, NJ, USA, 4-9 May 1998; pp. 69-73.
23. Clerc, M. The Swarm and the Queen: Towards a Deterministic and Adaptive Particle Swarm Optimization. In Proceedings of the Congress on Evolutionary Computation, Washington, DC, USA, 6-9 July 1999; pp. 1951-1957.
24. Eberhart, R.; Shi, Y. Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization. In Proceedings of the 2000 IEEE Congress on Evolutionary Computation, La Jolla, CA, USA, 16-19 July 2000; pp. 84-88.
25. Bratton, D.; Kennedy, J. Defining a Standard for Particle Swarm Optimization. In Proceedings of the 2007 IEEE Swarm Intelligence Symposium, Honolulu, HI, USA, 1-5 April 2007; pp. 120-127.
26. Clerc, M.; Kennedy, J. The particle swarm-Explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 2002, 6, 58-73.
27. Tsai, S.J.; Sun, T.Y.; Liu, C.C.; Hsieh, S.T.; Wu, W.C.; Chiu, S.Y. An improved multi-objective particle swarm optimizer for multi-objective problems. Expert Syst. Appl. 2010, 37, 5872-5886.