Formulation of low level heuristics

  • Abstract
  • Keywords
  • References
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  • Abstract

    The curricula scheduling is very significant and largely studied problem in academia. The desired solution calculatedly assembles the academic events over the carefully designed layout considering several predefined interlinked constraints. The contemporary research for solving scheduling constraints is inclined to raise the degree of generality, so that a wide range of identical problems may be addressed. The hyper-heuristic is such a state-of-the-art solving technique which stands on multi-layered framework. The top layer usually consists of classic algorithm for managing the operators on down-layers, and the same is occasionally assisted by machine learning or similar techniques. This research article examines the performance of the small group of bespoke low level heuristics. These LLHs are operated by hyper-heuristic to address the specific scheduling constraints. The set of heuristics are divided into a range of subgroups including timescale category which contain two subsets Day and Period. The utility group which contains two patterns named Shift and Swap techniques, while the third category encircles three more subgroups of Random or Sami-Random and Progressive.

  • Keywords

    Curricula Scheduling; Constraints; Low Level Heuristics.

  • References

      [1] Aftab Ahmed, Mazhar Ali, Walayat Hussain, and A. H. S. Bukhari, "Bespoke Set of Heuristics for Solving Curriculum Scheduling Problems " Sindh University Research Journal (Science Series), vol. 44, pp. 13-20, June 2012.

      [2] Aftab Ahmed and Z. Li, "A Biphasic Approach for University Timetabling Problem," in IEEE 2nd International Conference on Computer Engineering and Technology (ICCET 2010), Chengdu, Sichuan, China, 2010, pp. 192-197.

      [3] Aftab Ahmed and Z. Li, "Solving Course Timetabling Problem Using Interrelated Approach," in IEEE International Conference on Granular Computing San Jose, California, USA, 2010, pp. 651-655.

      [4] Aftab Ahmed, Mazhar Ali, Mirza Aamir Mehmood, and A. H. S. Bukhari, "Designing A Generic Layout For Acdemic Scheduling Problems," Australian Journal of Basic and Applied Sciences, vol. 5, pp. 1393-1397, 2011.

      [5] Aftab Ahmed, Ghulam Ali Mashori, and W. Hussain, "Prograssive Dataset Initlization of Curiculum Benchmark Scheduling " journal of Science, Technology, and Development, vol. 30, pp. 7-15, 2011.

      [6] Aftab Ahmed, Walayat Hussain, and A. Kamran, "Logic Formulation and Evaluation of Academic Constraints," International Journal of Basic and Applied Sciences, vol. 1, pp. 26-39, 2012.

      [7] G. O. Jorge A. Soria-Alcaraz, Jerry Swan, Martin Carpio, Hector Puga, Edmund K. Burke, "Effective learning hyper-heuristics for the course timetabling problem," European Journal of Operational Research, vol. 238, pp. 77–86, 2014.

      [8] Aftab Ahmed, Abdul Wahid Shaikh, Mazhar Ali, and A. H. S. Bukhari, "Hyper-GA for Solving Benchmark Scheduling Problems," Australian Journal of Basic and Applied Sciences, vol. 5, pp. 1657-1667, June 2011.

      [9] Alex Bonutti, Fabio De Cesco, Luca Di Gaspero, and A. Schaerf, "Benchmarking curriculum-based course timetabling: formulations, data formats, instances, validation, visualization, and results " Annals of Operations Research, vol. 179, 2010.

      [10] Aftab Ahmed, Ahthasham Sajid, Mazhar Ali, and A. H. S. Bukhari, "Particle Swarm Optimizatin Based Hyper-Heuristic For Tackling Real World Examinations Scheduling Problem," Australian Journal of Basic and Applied Sciences, vol. 5, pp. 1406-1413, 2011.

      [11] Aftab Ahmed, Riaz ul Amin, Muhammad Abbas Khan, and A. Sajid, "A Novel Set of Heuristics for Scheduling Constraints," in 3rd International Conference on Computer and Emerging Technologies (ICCET 2013) 2013.




Article ID: 4001
DOI: 10.14419/ijbas.v4i1.4001

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