User:Eugene M. Izhikevich/Proposed/Hyperheuristic

• Prof. Graham Kendall, School of Computer Science, University of Nottingham, UK

• Dr. Ender Özcan, School of Computer Science, University of Nottingham, UK

Prof. Graham Kendall and Dr. Ender Özcan accepted the invitation on 20 November 2009 (self-imposed deadline: 20 May 2010).

Definition

Work in Progess

History

Work in Progess

Classification

Work in Progess

Starting Points

In this section we provide a list of references which might be useful to those who are new to the area and are wondering what they should read first.

• Burke, Kendall and Soubeiga, 2003a
• Burke et al., 2003b
• Cowling, Kendall and Soubeiga, 2000
• Ross, 2005

External Links

• Author’s website (Graham Kendall)
• Author’s website (Ender Özcan)

• Hyper-heuristics in Wikipedia

References

• Bai R, Kendall G (2008) A Model for Fresh Produce Shelf-space Allocation and Inventory Management with Freshness-condition-dependent Demand. INFORMS Journal on Computing 20(1):78-85

• Burke EK, Kendall G. and Soubeiga E. (2003a) A Tabu-Search Hyper-Heuristic for Timetabling and Rostering. Journal of Heuristics, 9(6), 451-470, 2003 (doi: 10.1023/B:HEUR.0000012446.94732.b6)

• Burke EK, Hart E, Kendall G, Newall J, Ross P, Schulenburg S (2003b) Hyper-heuristics: An emerging direction in modern search technology. In: Glover F, Kochenberger G (eds) Handbook of Metaheuristics, Kluwer, 457-474

• Chakhlevitch K, Cowling PI (2008) Hyperheuristics: Recent developments. In: Cotta C, Sevaux M, SÄorensen K (eds) Adaptive and Multilevel Metaheuristics, Studies in Computational Intelligence, vol 136, Springer, 3-29

• Cowling P, Kendall G, Soubeiga E (2000) A hyperheuristic approach for scheduling a sales summit. In: Selected Papers of the Third International Conference on the Practice And Theory of Automated Timetabling, Lecture Notes in Computer Science, 176-190

• Crowston WB, Glover F, Thompson GL, Trawick JD (1963) Probabilistic and parametric learning combinations of local job shop scheduling rules. ONR Research memorandum, GSIA, Carnegie Mellon University, Pittsburgh -(117)

• Denzinger J, Fuchs M, Fuchs M (1997) High performance ATP systems by combining several ai methods. In: Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 102-107

• Fisher H, Thompson GL (1961) Probabilistic learning combinations of local job-shop scheduling rules. In: Factory Scheduling Conference, Carnegie Institue of Technology

• Fisher H, Thompson GL (1963) Probabilistic learning combinations of local job-shop scheduling rules. In: Muth JF, Thompson GL (eds) Industrial Scheduling, Prentice-Hall, Inc, New Jersey, 225-251

• Özcan E, Bilgin B, Korkmaz EE (2008) A comprehensive survey of hyper-heuristics. Intelligent Data Analysis 12(1):1-21

• Ross P (2005) Hyper-heuristics. In: Burke EK, Kendall G (eds) Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, Springer, chap 17, 529-556

• Pisinger D, Ropke S (2007) A general heuristic for vehicle routing problems. Computers and Operations Research 34, 2403-2435