User:Eugene M. Izhikevich/Proposed/Hyperheuristic

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



Work in Progess


Work in Progess


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


  • 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, 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
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