Skip to main content
SpringerLink
Log in

Landscapes, Embedded Paths and Evolutionary Scheduling

  • Chapter
Evolutionary Scheduling

Part of the book series: Studies in Computational Intelligence ((SCI,volume 49))

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Reeves CR (ed) (1993) Modern Heuristic Techniques for Combinatorial Problems. Blackwell Scientific Publications, Oxford, UK (Re-issued by McGraw-Hill, London, UK (1995).)

    MATH  Google Scholar 

  2. Aarts E, Lenstra JK (eds) (1997) Local Search in Combinatorial Optimization. John Wiley & Sons, Chichester

    MATH  Google Scholar 

  3. Glover F, Kochenberger GA (eds) (2002) Handbook of Metaheuristics, Kluwer Academic Publishers, Norwell, MA

    Google Scholar 

  4. Burke EK, Kendall G (eds) (2005) Search Methodologies: Introductory Tutorials in Optimization and Decision Support Methodologies. Springer, New York

    MATH  Google Scholar 

  5. Morton TE, Pentico DW (1993) Heuristic Scheduling Systems, Wiley, NY

    Google Scholar 

  6. Stadler PF (1995) Towards a theory of landscapes. In: Lopéz-Peña R, Capovilla R, García-Pelayo R, Waelbroeck H, Zertuche F (eds) Complex Systems and Binary Networks. Springer, Berlin

    Google Scholar 

  7. Reeves CR, Rowe JE (2002) Genetic Algorithms Principles and Perspectives. Kluwer Academic Publishers, Norwell, MA

    Google Scholar 

  8. Reeves CR (2005) Fitness Landscapes In: Burke EK, Kendall G (eds) (2005) Search Methodologies: Introductory Tutorials in Optimization and Decision Support Methodologies. Springer, New York

    Google Scholar 

  9. Johnson DS (1990) Local optimization and the traveling salesman problem. In: Goos G, Hartmanis J (eds) (1990) Automata, Languages and Programming, Lecture Notes in Computer Science 443. Springer, Berlin

    Google Scholar 

  10. Glover F, Laguna M (1993) Tabu Search. In: Reeves CR (ed) (1993) Modern Heuristic Techniques for Combinatorial Problems. Blackwell Scientific Publications, Oxford, UK

    Google Scholar 

  11. Reeves CR, Yamada T (1999) Goal-Oriented path tracing methods. In: Corne DA, Dorigo M, Glover F (eds) (1999) New Methods in Optimization, McGrawHill, London

    Google Scholar 

  12. Holland JH (1986) Escaping brittleness: The possibilities of general-purpose learning algorithms applied to parallel rule-based systems. In: Michalski RS, Carbonell JG, Mitchell TM (1986) Machine Learning II. Morgan Kaufmann, Los Altos, CA

    Google Scholar 

  13. Reeves CR (2003) The ‘crossover landscape’ and the Hamming landscape for binary search spaces. In: De Jong KA, Poli R, Rowe JE (eds.) Foundations of Genetic Algorithms 7. Morgan Kaufmann, San Francisco, CA

    Google Scholar 

  14. Boese KD, Kahng AB, Muddu S (1994) Operations Research Letters 16:101-113

    Article  MATH  MathSciNet  Google Scholar 

  15. Reeves CR (1999) Annals of Operational Research 86:473-490

    Article  MATH  MathSciNet  Google Scholar 

  16. Merz P, Freisleben B (1998) Memetic algorithms and the fitness landscape of the graph bi-partitioning problem. In: Eiben AE, Bäck T, Schoenauer M, Schwefel H-P (eds) (1998) Parallel Problem-Solving from Nature—PPSN. Springer, Berlin

    Google Scholar 

  17. Kauffman S (1993) The Origins of Order: Self-Organisation and Selection in Evolution. Oxford University Press, Oxford

    Google Scholar 

  18. Taillard E (1993) European J Operational Research 64:278-285

    Article  MATH  Google Scholar 

  19. Schiavinotto T, Stützle T (2006) To appear in: Computers and Operations Research. (Available online at doi:10.1016/j.cor.2005.11.022)

    Google Scholar 

  20. Reeves CR, Yamada T (1998) Evolutionary Computation 6:45-60

    Article  Google Scholar 

  21. Levenhagen J, Bortfeldt A, Gehring H (2001) Path tracing in genetic algorithms applied to the multiconstrained knapsack problem. In: Boers EJW et al. (eds) Applications of Evolutionary Computing. Springer, Berlin

    Google Scholar 

  22. Watson J-P, Barbulescu L, Whitley LD, Howe AE (2002) INFORMS J Computing 14: 98-123

    Article  MathSciNet  Google Scholar 

  23. Grabowski J, Wodecki, M (2004) Computers and Operations Research 31:1891-1909

    Article  MATH  MathSciNet  Google Scholar 

  24. Wang C, Chu C, Proth J (1997) European J Operational Research 96:636-644

    Article  MATH  Google Scholar 

  25. Liu J, Reeves CR (2001) European J Operational Research 132:439-452

    Article  MATH  MathSciNet  Google Scholar 

  26. Yamada T, Reeves CR (1998) Solving the Csum permutation flowshop scheduling problem by genetic local search. In: Proc. of 1998 International Conference on Evolutionary Computation, 230 234. IEEE Press

    Google Scholar 

  27. Rinnooy Kan AHG (1976) Machine Scheduling Problems: Classification, Complexity and Computations. Martinus Nijhoff, The Hague, NL

    Google Scholar 

  28. Reeves CR (1995) Computers & Operations Research 22:5-13

    Article  MATH  Google Scholar 

  29. McGrath A (2005) Dawkins’ God: Genes, Memes and the Meaning of Life. Blackwell, Oxford, UK.

    Google Scholar 

  30. Weinberger ED (1990) Biological Cybernetics 63:325-336

    Article  MATH  Google Scholar 

  31. Reeves CR, Eremeev AV (2004) J Operational Research Society 55:687-693

    Article  MATH  Google Scholar 

  32. Reeves CR, Aupetit-Bélaidouni MM (2004) Estimating the number of solutions for SAT problems. In Yao X et al. (eds.) (2004) Parallel Problem-Solving from Nature—PPSN VIII, LNCS3242. Springer, Berlin

    Google Scholar 

  33. Reidys CM, Stadler PF (2002) SIAM Review 44:3-54

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Applied Mathematics Research Centre Department of Mathematical Sciences, Coventry University, Coventry, UK

    Colin R. Reeves

Authors
  1. Colin R. Reeves
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Modeling Optimisation Scheduling and Intelligent Control (MOSAIC), Research Centre, Department of Computing, University of Bradford, West Yorkshire, BD7 1DP, Bradford, UK

    Keshav P. Dahal

  2. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, Singapore

    Kay Chen Tan

  3. Modeling Optimisation Scheduling and Intelligent Control (MOSAIC), Research Centre, Department of Computing, University of Bradford, West Yorkshire, BD7 1DP, Bradford, UK

    Peter I. Cowling

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Reeves, C.R. (2007). Landscapes, Embedded Paths and Evolutionary Scheduling. In: Dahal, K.P., Tan, K.C., Cowling, P.I. (eds) Evolutionary Scheduling. Studies in Computational Intelligence, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48584-1_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-48584-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-48582-7

  • Online ISBN: 978-3-540-48584-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation