Skip to main content
SpringerLink
Log in

The multi-alternative cargo routing problem: Solution by evolutionary methods

  • Control Systems and Information Technologies
  • Published:
Automation and Remote Control Aims and scope Submit manuscript

Abstract

This paper presents a rigorous formulation of the multi-alternative routing problem. The memetic algorithm yielding a global transportation plan is developed. We propose an algorithm constructing the optimal path among nodes of a road graph. Finally, the modular structure of the routing subsystem is designed and implemented.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Johnson, D.S. and McGeoch, L.A., The Traveling Salesman Problem: A Case Study in Local Optimization, in Local Search in Combinatorial Optimization, Aarts, E. and Lenstra, J.K., Eds., Princeton: Princeton Univ. Press, 1997, pp. 215–310.

    Google Scholar 

  2. Podvalniy, S.L., Multi-alternative Systems: A Review and Classification, Sist. Upravlen. Inform. Tekhn., 2012, vol. 48, no. 2, pp. 4–13.

    Google Scholar 

  3. Russell S.J. and Norvig, P., Artificial Intelligence: A Modern Approach, Upper Saddle River: Prentice Hall, 2009.

    Google Scholar 

  4. Anderson, J.A., Discrete Mathematics with Combinatorics, Upper Saddle River: Pearson Education, 2004. Translated under the title Diskretnaya matematika i kombinatorika, Moscow: Vil’yams, 2006.

    Google Scholar 

  5. Kravets, O.Ya. and Kulishenko, V.S., Features of Program Realization of Control Workbenches for Territorially Distributed Flows of Requests, Sist. Upravlen. Inform. Tekhn., 2011, vol. 45, no. 3.2, pp. 280–285.

    Google Scholar 

  6. Chen, X.S. et al. A Multi-Facet Survey on Memetic Computation, IEEE Trans. Evolut. Comput., 2011, vol. 15, no. 5, pp. 591–607.

    Article  Google Scholar 

  7. Batishchev, D.I., Reshenie diskretnykh zadach s pomoshch’yu evolyutsionno-geneticheskikh algoritmov (Solution of Discrete Problems by Evolutionary Genetic Algorithms), Nizhni Novgorod: Nizhegorod. Gos. Univ., 2011.

    Google Scholar 

  8. Dorigo, M. and Stützle, T., Ant Colony Optimization, Cambridge: MIT Press, 2004.

    Book  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Voronezh State Technical University, Voronezh, Russia

    O. A. Plotnikov

  2. Voronezh Branch, The Russian Presidential Academy of National Economy and Public Administration (RANEPA), Voronezh, Russia

    E. S. Podvalniy

Authors
  1. O. A. Plotnikov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E. S. Podvalniy
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

Original Russian Text © O.A. Plotnikov, E.S. Podvalniy, 2013, published in Sistemy Upravleniya i Informatsionnye Tekhnologii, 2013, No. 1, pp. 187–192.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Plotnikov, O.A., Podvalniy, E.S. The multi-alternative cargo routing problem: Solution by evolutionary methods. Autom Remote Control 74, 1753–1760 (2013). https://doi.org/10.1134/S0005117913100147

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0005117913100147

Keywords

Search

Navigation