Abstract
This paper investigates an emerging class of search algorithms, in which high-level domain independent heuristics, called hyper-heuristics, iteratively select and execute a set of application specific but simple search moves, called low-level heuristics, working toward achieving improved or even optimal solutions. Parallel architectures have been designed and evaluated. Results based on a university timetabling problem show an important relationship between performance, algorithm software and hardware implementation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abramson, D.: Constructing School Timetables using Simulated Annealing: Sequential and Parallel Algorithms. Manage. Sci. 37, 98–113 (1991)
Abramson, D., Abela, J.: A Parallel Genetic Algorithm for Solving the School Timetabling Problem. In: Proc. 15th Australian Computer Science Conference (ACSC-15), vol. 14, pp. 1–11 (1992)
Ayob, M., Kendall, G.: A Monte Carlo Hyper-heuristic To Optimise Component Placement Sequencing For Multi Head Placement Machine. In: Proc. Int. Conf. on Intelligent Technologies (InTech 2003), Chiang Mai, Thailand, December 17–19, pp. 132–141 (2003)
Bullnheimer, B., Kotsis, G., Strauss, C.: Parallelization Strategies for the Ant System. In: High Performance Algorithms and Software in Nonlinear Optimization. Applied Optimization Series, vol. 24, pp. 87–100. Kluwer, Dordrecht (1998)
Burke, E.K., Dror, M., Petrovic, S., Qu, R.: Hybrid Graph Heuristics within a Hyper-heuristic Approach to Exam Timetabling Problems. In: Golden, B.L., Raghavan, S., Wasil, E.A. (eds.) The Next Wave in Computing, Optimization, and Decision Technologies. Conference Volume of the 9th INFORMS Computing Society Conference, pp. 79–91. Springer, Berlin (2005)
Burke, E.K., Hart, E., Kendall, G., Newall, J., Ross, P., Schulenburg, S.: Hyper-Heuristics: An Emerging Direction in Modern Search Technology. In: Glover, F., Kochenberger, G. (eds.) Handbook of Meta-Heuristics, ch. 16, pp. 457–474. Kluwer, Dordrecht (2003)
Burke, E.K., Kendall, G., Soubeiga, E.: A Tabu Search Hyper-heuristic for Timetabling and Rostering. J. Heuristics 9, 451–470 (2003)
Burke, E.K., Landa Silva, J.D., Soubeiga, E.: Multi-objective Hyper-heuristic Approaches for Space Allocation and Timetabling. In: Ibaraki, T., Nonobe, K., Yagiura, M. (eds.) Meta-heuristics: Progress as Real Problem Solvers. Springer, Berlin (2005) (to appear)
Burke, E.K., MacCarthy, B.L., Petrovic, S., Qu, R.: Knowledge Discovery in Hyper-heuristic Using Case-based Reasoning on Course Timetabling. In: Burke, E.K., De Causmaecker, P. (eds.) PATAT 2002. LNCS, vol. 2740, pp. 276–287. Springer, Heidelberg (2003)
Burke, E.K., Meisels, A., Petrovic, S., Qu, R.: A Graph-Based Hyper Heuristic for Timetabling Problems. Eur. J. Oper. Res. (2005) (accepted for publication)
Burke, E.K., Newall, J.P.: Solving Examination Timetabling Problems through Adaption of Heuristic Orderings. Ann. Oper. Res. 129, 107–134 (2004)
Cantu-Paz, E.: A Survey of Parallel Genetic Algorithms. Calculateurs Paralleles, Reseaux Syst. Repartis 10, 141–171 (1998)
Cowling, P., Kendall, G., Han, L.: An Investigation of a Hyperheuristic Genetic Algorithm Applied to a Trainer Scheduling Problem. In: Proc. Congress on Evolutionary Computation, CEC 2002, Honolulu, Hawaii, May 12–17, pp. 1185–1190 (2002)
Cowling, P., Kendall, G., Soubeiga, E.: A Hyperheuristic Approach to Scheduling a Sales Summit. In: Burke, E., Erben, W. (eds.) PATAT 2000. LNCS, vol. 2079, pp. 176–190. Springer, Heidelberg (2001)
Cowling, P., Kendall, G., Soubeiga, E.: A Parameter-Free Hyperheuristic for Scheduling a Sales Summit. In: Proc. 4th Metaheuristics Int. Conf., MIC 2001, Porto, Portugal, pp. 127–131 (2001)
Cowling, P., Kendall, G., Soubeiga, E.: Hyperheuristics: A Tool for Rapid Prototyping in Scheduling and Optimisation. In: Cagnoni, S., Gottlieb, J., Hart, E., Middendorf, M., Raidl, G.R. (eds.) EvoIASP 2002, EvoWorkshops 2002, EvoSTIM 2002, EvoCOP 2002, and EvoPlan 2002. LNCS, vol. 2279, pp. 1–10. Springer, Heidelberg (2002)
De Falco, I., Del Balio, R., Tarantino, E.: Solving the Mapping Problem by Parallel Tabu Search. Technical Report. Instituto per la Ricerca sui Sistemi Informatici Paralli, Italy (1996)
Han, L., Kendall, G.: Guided Operators for a Hyper-Heuristic Genetic Algorithm. In: Gedeon, T(T.) D., Fung, L.C.C. (eds.) AI 2003. LNCS (LNAI), vol. 2903, pp. 807–820. Springer, Heidelberg (2003)
Han, L., Kendall, G.: Investigation of a Tabu Assisted Hyper-Heuristic Genetic Algorithm. In: Proc. Congress on Evolutionary Computation, CEC 2003, Canberra, Australia, vol. 3, pp. 2230–2237 (2003)
Kendall, G., Mohd Hussin, N.: An Investigation of a Tabu Search Based Hyper-heuristic for Examination Timetabling. In: Kendall, G., Burke, E., Petrovic, S., Gendreau, M. (eds.) Multi-disciplinary Scheduling: Theory and Applications I (MISTA 2003) Selected Papers, pp. 309–328. Springer, Berlin (2005)
Kendall, G., Mohd Hussin, N.: Tabu Search Hyper-heuristic Approach to the Examination Timetabling Problem at the MARA University of Technology. In: Burke, E.K., Trick, M.A. (eds.) PATAT 2004. LNCS, vol. 3616, pp. 270–293. Springer, Heidelberg (2005)
Petrovic, S., Qu, R.: Case-Based Reasoning as a Heuristic Selector in a Hyper-Heuristic for Course Timetabling Problems. In: Proc. Knowledge-Based Intelligent Information Engineering Systems and Allied Technologies, vol. 82, pp. 336–340 (2002)
Randall, M., Abramson, D.: A General Parallel Tabu Search Algorithm for Combinatorial Optimisation Problems. In: Proc. 1999 Parallel and Real Time Conference, Melbourne, Australia, pp. 68–79 (1999)
Ross, P., Marín-Blázquez, J.G., Schulenburg, S., Hart, E.: Learning a Procedure That Can Solve Hard Bin-Packing Problems: A New GA-Based Approach to Hyper-heuristics. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2724, pp. 1295–1306. Springer, Heidelberg (2003)
Ross, P., Schulenburg, S., Marín-Blázquez, J.G., Hart, E.: Hyper-heuristics: Learning to Combine Simple Heuristics in Bin-Packing Problems. In: Proc. of the Genetic and Evolutionary Computation Conference (GECCO 2002), New York, pp. 942–948 (2000)
Socha, K., Knowles, J., Sampels, M.: A Max–Min Ant System for the University Course Timetabling Problem. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) Ant Algorithms 2002. LNCS, vol. 2463, pp. 1–13. Springer, Heidelberg (2002) (Also Technical Report TR/IRIDIA/2002-18)
Soubeiga, E.: Development and Application of Hyperheuristics to Personnel Scheduling, Ph.D Thesis. University of Nottingham (2003)
Terashima-Marin, H., Ross, P.M., Valenzuela-Rendon, M.: Evolution of Constraint Satisfaction Strategies in Examination Timetabling. In: Banzhaf, W., et al. (eds.) Proc. Genetic and Evolutionary Computation Conference (GECCO 1999), pp. 635–642. Morgan Kaufmann, San Mateo (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rattadilok, P., Gaw, A., Kwan, R.S.K. (2005). Distributed Choice Function Hyper-heuristics for Timetabling and Scheduling. In: Burke, E., Trick, M. (eds) Practice and Theory of Automated Timetabling V. PATAT 2004. Lecture Notes in Computer Science, vol 3616. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11593577_4
Download citation
DOI: https://doi.org/10.1007/11593577_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30705-1
Online ISBN: 978-3-540-32421-8
eBook Packages: Computer ScienceComputer Science (R0)