Introducing a Novel Parameter in Generation of Course Timetable with Genetic Algorithm

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 258)

Abstract

In this paper, we introduce a new Happiness parameter along with Genetic Algorithm for generating course timetable. This happiness parameter will generate appropriately feasible solution and account for the comfort and happiness of the instructor and students both (indicating the appropriateness of the resulting solution). The final result obtained from this approach shows that the solution space is reduced considerably and hence a feasible solution is obtained. Using this parameter, it can also be analysed that the solution obtained from Genetic Algorithm without Happiness Parameter are unfavourable most of the times. We perform experiments on data of Department of Computer Engineering, G.B. Pant University of Agriculture and Technology, Pantnagar and are able to produce promising results.

Keywords

Genetic algorithm Timetable Scheduling Happiness parameter 

References

  1. 1.
    Cooper, T.B., Kingston, J.H.: The complexity of timetable construction problems. In: Burke, Edmund, Ross, Peter (eds.) Practice and Theory of Automated Timetabling. Lecture Notes in Computer Science, vol. 1153, pp. 281–295. Springer, Berlin (1996)CrossRefGoogle Scholar
  2. 2.
    Hosny, M., Fatima, S.: A survey of genetic algorithms for the university timetabling problem. In: International Proceedings of Computer Science and Information Technology, vol. 13, (2011)Google Scholar
  3. 3.
    Corne, D., Ross, P.: Peckish initialisation strategies for evolutionary timetabling. In: Selected papers from the First International Conference on Practice and Theory of Automated Timetabling, pp. 227–240. Springer, London (1996) Google Scholar
  4. 4.
    Zibran, M.F.: A Multi-phase Approach to University Course Timetabling. University of Lethbridge, Canada (2007). Canadian thesesGoogle Scholar
  5. 5.
    Lewis, R., Paechter, B.: Finding feasible timetables using group-based operators. IEEE Trans. Evol. Comput. 11(3), 397–413 (2007)CrossRefGoogle Scholar
  6. 6.
    Bambrick, L.: Lecture Timetabling Using Genetic Algorithms. The University of Queensland, Brisbane (1997)Google Scholar
  7. 7.
    Abdullah, S., Turabieh, H.: Generating university course timetable using genetic algorithms and local search. In: 3rd International Conference on Convergence and Hybrid Information Technology, 2008. ICCIT ‘08, vol. 1, pp. 254–260. (2008)Google Scholar
  8. 8.
    Yang, S., Jat, S.N.: Genetic algorithms with guided and local search strategies for university course timetabling. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 41(1), 93–106 (2011)Google Scholar
  9. 9.
    Hacker, K.A., Eddy, J., Lewis, K.E.: Efficient global optimization using hybrid genetic algorithms. In: 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pp. 4–6. (2002)Google Scholar
  10. 10.
    Holland, J.H.: Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press, Michigan (1975)Google Scholar
  11. 11.
    Davis, L.: Handbook of genetic algorithms. VNR computer library. Van Nostrand Reinhold, New york (1991)Google Scholar
  12. 12.
    Abdullah, S., Turabieh, H., McCollum, B., Burke, E.K.: An investigation of a genetic algorithm and sequential local search approach for curriculum-based course timetabling problems. In: Proceedings of Multidisciplinary International Conference on Scheduling: Theory and Applications (MISTA 2009), Ireland, pp. 727–731. (2009)Google Scholar
  13. 13.
    Sapru, V., Reddy, K., Sivaselvan, B.: Time table scheduling using genetic algorithms employing guided mutation. In: IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 2010, pp. 1–4. (2010)Google Scholar
  14. 14.
    Gen, M., Cheng, R.: Genetic algorithms and engineering design (engineering design and automation). Wiley, New York (1997)Google Scholar

Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Computer EngineeringG.B. Pant University of Agriculure and TechnologyPantnagarIndia

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