Skip to main content
SpringerLink
Log in

Ant Colony Optimization with Immigrants Schemes for the Dynamic Vehicle Routing Problem

  • Conference paper
Applications of Evolutionary Computation (EvoApplications 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7248))

Included in the following conference series:

Abstract

Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when they are enhanced to maintain diversity and transfer knowledge. Several approaches have been integrated with ACO to improve its performance for DOPs. Among these integrations, the ACO algorithm with immigrants schemes has shown good results on the dynamic travelling salesman problem. In this paper, we investigate ACO algorithms to solve a more realistic DOP, the dynamic vehicle routing problem (DVRP) with traffic factors. Random immigrants and elitism-based immigrants are applied to ACO algorithms, which are then investigated on different DVRP test cases. The results show that the proposed ACO algorithms achieve promising results, especially when elitism-based immigrants are used.

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 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. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York (1999)

    MATH  Google Scholar 

  2. Dorigo, M., Maniezzo, V., Colorni, A.: Ant system: optimization by a colony of cooperating agents. IEEE Trans. on Syst. Man and Cybern. Part B: Cybern. 26(1), 29–41 (1996)

    Article  Google Scholar 

  3. Dorigo, M., Stützle, T.: Ant Colony Optimization. The MIT Press, London (2004)

    Book  MATH  Google Scholar 

  4. Eyckelhof, C.J., Snoek, M.: Ant Systems for a Dynamic TSP. In: ANTS 2002: Proc. of the 3rd Int. Workshop on Ant Algorithms, pp. 88–99 (2002)

    Google Scholar 

  5. Gambardella, L.M., Taillard, E., Agazzi, G.: MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows. In: Corne, D., et al. (eds.) New Ideas in Optimization, pp. 63–76 (1999)

    Google Scholar 

  6. Guntsch, M., Middendorf, M.: Applying Population Based ACO to Dynamic Optimization Problems. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) Ant Algorithms 2002. LNCS, vol. 2463, pp. 111–122. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  7. Guntsch, M., Middendorf, M.: Pheromone Modification Strategies for Ant Algorithms Applied to Dynamic TSP. In: Boers, E.J.W., Gottlieb, J., Lanzi, P.L., Smith, R.E., Cagnoni, S., Hart, E., Raidl, G.R., Tijink, H. (eds.) EvoIASP 2001, EvoWorkshops 2001, EvoFlight 2001, EvoSTIM 2001, EvoCOP 2001, and EvoLearn 2001. LNCS, vol. 2037, pp. 213–222. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  8. Tao, G., Michalewicz, Z.: Inver-over Operator for the TSP. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.-P. (eds.) PPSN 1998. LNCS, vol. 1498, pp. 803–812. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  9. Jin, Y., Branke, J.: Evolutionary optimization in uncertain environments - a survey. IEEE Trans. on Evol. Comput. 9(3), 303–317 (2005)

    Article  Google Scholar 

  10. Labbe, M., Laporte, G., Mercure, H.: Capacitated vehicle routing on trees. Operations Research 39(4), 616–622 (1991)

    Article  MATH  Google Scholar 

  11. Mavrovouniotis, M., Yang, S.: Ant Colony Optimization with Immigrants Schemes in Dynamic Environments. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds.) PPSN XI. LNCS, vol. 6239, pp. 371–380. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  12. Mavrovouniotis, M., Yang, S.: Memory-Based Immigrants for Ant Colony Optimization in Changing Environments. In: Di Chio, C., Cagnoni, S., Cotta, C., Ebner, M., Ekárt, A., Esparcia-Alcázar, A.I., Merelo, J.J., Neri, F., Preuss, M., Richter, H., Togelius, J., Yannakakis, G.N. (eds.) EvoApplications 2011, Part I. LNCS, vol. 6624, pp. 324–333. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  13. Montemanni, R., Gambardella, L., Rizzoli, A., Donati, A.: Ant colony system for a dynamic vehicle routing problem. Journal of Combinatorial Optimization 10(4), 327–343 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  14. Psaraftis, H.: Dynamic vehicle routing: status and prospects. Annals of Operations Research 61, 143–164 (1995)

    Article  MATH  Google Scholar 

  15. Rizzoli, A.E., Montemanni, R., Lucibello, E., Gambardella, L.M.: Ant colony optimization for real-world vehicle routing problems - from theory to applications. Swarm Intelli. 1(2), 135–151 (2007)

    Article  Google Scholar 

  16. Yang, S.: Genetic algorithms with memory and elitism based immigrants in dynamic environments. Evol. Comput. 16(3), 385–416 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Leicester, University Road, Leicester, LE1 7RH, United Kingdom

    Michalis Mavrovouniotis

  2. Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UB8 3PH, United Kingdom

    Shengxiang Yang

Authors
  1. Michalis Mavrovouniotis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shengxiang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 16 Richmond Street, G1 1XQ, Glasgow, UK

    Cecilia Di Chio

  2. Financial Mathematics and Computation Cluster Natural Computing Research and Applications Group Complex and Adaptive Systems Laboratory, University College, Dublin, Ireland

    Alexandros Agapitos

  3. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  4. ETSI Informática, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  5. Centro Universitario de Merida, Universidad de Extremadura, Spain

    Francisco Fernández de Vega

  6. Dalle Molle Institute for Artificial Intelligence (IDSIA), Lugano, Switzerland

    Gianni A. Di Caro

  7. DFKI Bremen, Cyber-Physical Systems, Bremen, Germany

    Rolf Drechsler

  8. Knowledge Engineering Research Group, Aston University, B4 7ET, Aston Triangle, Birmingham, UK

    Anikó Ekárt

  9. Instituto Tecnológico de Informática, Edif. 8G Acceso B, Universidad Politécnica de Valencia, 46022, Valencia, Spain

    Anna I. Esparcia-Alcázar

  10. Next Generation Intelligent Networks Research Center (nexGIN RC), National University of Computer & Emerging Sciences (FAST-NU), Islamabad, Pakistan

    Muddassar Farooq

  11. Department of Computer Science,, University College London, Gower Street, WC1E 6BT, London, UK

    William B. Langdon

  12. Depto. Arquitectura y Tecnologa de Computadores, ETS Ingeiera Informtica, C/Daniel Saucedo Aranda, s/n, 18071, Granada, Spain

    Juan J. Merelo-Guervós

  13. Chair of Algorithm Engineering, Computational Intelligence Group, Dept. of Computer Science, Technische Universität Dortmund, Germany

    Mike Preuss

  14. HTWK Leipzig, Fakultät Elektrotechnik und Informationstechnik, Institut Mess–, Steuerungs– und Regelungstechnik, Postfach 30 11 66, D–04251, Leipzig, Germany

    Hendrik Richter

  15. INESC-ID Lisboa, Rua Alves Redol 9,, 1000-029, Lisboa, Portugal

    Sara Silva

  16. Centre for Informatics and Systems, University of Coimbra, Portugal

    Anabela Simões

  17. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

  18. Institute of High Performance Computing and Networking, ICAR-CNR, Naples, Italy

    Ernesto Tarantino

  19. Dipartimento di Tecnologie dell’Informazione, Universita’ degli Studi di Milano, Italy

    Andrea G. B. Tettamanzi

  20. IT University of Copenhagen, Rued Langaards Vej 7, 2300, Copenhagen, Denmark

    Julian Togelius

  21. Centre for Emergent Computing, Edinburgh Napier University, Edinburgh,, UK

    Neil Urquhart

  22. Department of Computer Engineering, Istanbul Technical University, 34490, Maslak, Turkey

    A. Åžima Uyar

  23. Center For Computer Games Research, IT University Of Copenhagen, Rued Langgaards Vej 7, 2300, Copenhagen, Denmark

    Georgios N. Yannakakis

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mavrovouniotis, M., Yang, S. (2012). Ant Colony Optimization with Immigrants Schemes for the Dynamic Vehicle Routing Problem. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2012. Lecture Notes in Computer Science, vol 7248. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29178-4_52

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29178-4_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29177-7

  • Online ISBN: 978-3-642-29178-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation