Skip to main content

An Immune Inspired Algorithm for Solving Dynamic Vehicle Dispatching Problem in a Port Container Terminal

  • Conference paper
Artificial Immune Systems (ICARIS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5666))

Included in the following conference series:

Abstract

A typical Vehicle Dispatching Problem (VDP) for a port container terminal often involves offline resource allocation and is often successfully solved by heuristics algorithms. In this research, an autonomous and decentralized vehicle dispatching algorithm is proposed in which the algorithm is inspired by the human immune system. Specifically, the proposed algorithm is inspired by the cell-mediate immune response of T-cells that possess the capability of exploring the environment and providing an adaptive and specific immune response to the invading antigens. We conduct extensive simulation studies to study the performance of the algorithm in solving a typical vehicle dispatch problem derived from realistic terminal configurations and operational constraints. The results show good vehicle utilization and low computational cost when comparing with a GA-based algorithm.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. de Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, Heidelberg (2002)

    MATH  Google Scholar 

  2. Hart, E., Timmis, J.: Application areas of AIS: the past, the present and the future. Applied Soft Computing 8, 191–201 (2008)

    Article  Google Scholar 

  3. Grunow, M., Gunter, H.O., Lehmann, M.: Dispatching multi-load AGVs in highly automated seaport container terminals. OR Spectrum 26, 211–235 (2004)

    Article  MATH  Google Scholar 

  4. Kim, K.H., Bae, J.W.: A look-ahead dispatching method for automated guided vehicles in automated port container terminals. Informs(Transportation Science) 38(2), 224–234 (2004)

    Google Scholar 

  5. Bish, E.K., Chen, F.Y., Leong, Y.T., Nelson, B.L., Ng, J.W.C., Simchi-Levi, D.: Dispatching vehicles in a mega container terminal. OR Spectrum 27, 491–506 (2005)

    Article  MATH  Google Scholar 

  6. Gendreau, M., Guertin, F., Potvin, J.Y., Seguin, R.: Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and delivers. Transportation Research Part C 14, 157–174 (2006)

    Article  Google Scholar 

  7. Potvin, J.V.: A review of bio-inspired algorithms for vehicle routing. Bio-inspired Algorithm for the Vehicle Routing Problem, SCI 161, 1–34 (2009)

    Article  Google Scholar 

  8. Silva, C.A., Sousa, J.M.C., Runkler, T.A.: Rescheduling and optimizing of logistics processes using GA and ACO. Engineering Applications of Artificial Intelligence 21(3), 343–352 (2008)

    Article  Google Scholar 

  9. Gambardealla, L.M., Taillard, E., Agazzim, G.: MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows, New Ideas in Optimization, pp. 63–76. McGraw-Hill, New York (1999)

    Google Scholar 

  10. Skrlec, D., Filipec, M., Krajcar, S.: A heuristic modification of genetic algorithm used for solving the single depot capacited vehicle routing problem. In: IEEE Proceedings on Intelligent Information Systems, pp. 184–188 (1997)

    Google Scholar 

  11. Zhao, F.G., Sun, J.S., Liu, W.M.: A hybrid genetic algorithm for the traveling salesman problem with pickup and delivery. International Journal of Automation and Computing, 97–102 (2009)

    Google Scholar 

  12. Lau, H.Y.K., Wong, V.W.K., Lee, I.S.K.: An immunity approach to strategic behavioral control. Engineering Applications of Artificial Intelligence 20(3), 289–306 (2007)

    Article  Google Scholar 

  13. Masutti, T.A.S., de Castro, L.N.: A Neuro-Immune Algorithm to solve the capacitated vehicle routing problem. In: Bentley, P.J., Lee, D., Jung, S. (eds.) ICARIS 2008. LNCS, vol. 5132, pp. 210–219. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  14. Jerne, N.: Towards a network theory of the immune system. Ann. Immunology 125C, 373–389 (1974)

    Google Scholar 

  15. Na, D., Lee, D.: Mathematical modeling of immune suppression. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) ICARIS 2005. LNCS, vol. 3627, pp. 182–192. Springer, Heidelberg (2005)

    Google Scholar 

  16. Wierzchon, S.T.: Idiotypic networks as a metaphor for data analysis algorithm. In: Saeed, K., Pejas, J. (eds.) Information Proceeding and Security Systems, pp. 389–400. Springer, US (2005)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lee, N.M.Y., Lau, H.Y.K., Ko, A.W.Y. (2009). An Immune Inspired Algorithm for Solving Dynamic Vehicle Dispatching Problem in a Port Container Terminal. In: Andrews, P.S., et al. Artificial Immune Systems. ICARIS 2009. Lecture Notes in Computer Science, vol 5666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03246-2_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-03246-2_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03245-5

  • Online ISBN: 978-3-642-03246-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics