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A Column Generation Heuristic for the General Vehicle Routing Problem

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Learning and Intelligent Optimization (LION 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6073))

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Abstract

This paper presents a column generation heuristic for the general vehicle routing problem (GVRP), a combined load acceptance and rich vehicle routing problem incorporating various real-life complexities. Computational experiments show that proposed column generation heuristic is competitive with heuristics previously presented for the GVRP.

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References

  1. Goel, A.: Fleet Telematics - Real-time Management and Planning of Commercial Vehicle Operations. In: Operations Research/Computer Science Interfaces, vol. 40. Springer, Heidelberg (2007)

    Google Scholar 

  2. Goel, A., Gruhn, V.: A general vehicle routing problem. European Journal of Operational Research 191(3), 650–660 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  3. Toth, P., Vigo, D.: The Vehicle Routing Problem. In: SIAM Monographs on Discrete Mathematics and Applications, Philadelphia (2002)

    Google Scholar 

  4. Bräysy, O., Gendreau, M.: Vehicle routing problem with time windows, Part I: Route construction and local search algorithms. Transportation Science 39(1), 104–118 (2005)

    Article  Google Scholar 

  5. Bräysy, O., Gendreau, M.: Vehicle routing problem with time windows, Part II: Metaheuristics. Transportation Science 39(1), 119–139 (2005)

    Article  Google Scholar 

  6. Desrochers, M., Desrosiers, J., Solomon, M.: New optimization algorithm for the vehicle routing problem with time windows. Operations Research 40(2), 342–354 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  7. Chen, Z.L., Xu, H.: Dynamic column generation for dynamic vehicle routing with time windows. Transportation Science 40(1), 74–88 (2006)

    Article  Google Scholar 

  8. Baldacci, R., Battarra, M., Vigo, D.: Routing a heterogeneous fleet of vehicles. Technical report DEIS OR.INGCE 2007/1, DEIS, University Bologna, Italy (2007)

    Google Scholar 

  9. Choi, E., Tcha, D.W.: A column generation approach to the heterogeneous fleet vehicle routing problem. Computers & Operations Research 34, 2080–2095 (2007)

    Article  MATH  Google Scholar 

  10. Mitrović-Minić, S.: Pickup and delivery problem with time windows: A survey. Technical report TR 1998-12, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada (1998)

    Google Scholar 

  11. Desaulniers, G., Desrosiers, J., Erdmann, A., Solomon, M., Soumis, F.: VRP with pickup and delivery. In: Toth, P., Vigo, D. (eds.) The Vehicle Routing Problem. SIAM Monographs on Discrete Mathematics and Applications, Philadelphia, pp. 225–242 (2002)

    Google Scholar 

  12. Savelsbergh, M., Sol, M.: DRIVE: dynamic routing of independent vehicles. Operations Research 46, 474–490 (1998)

    Article  MATH  Google Scholar 

  13. Savelsbergh, M., Sol, M.: The general pickup and delivery problem. Transportation Science 29(1), 17–30 (1995)

    Article  MATH  Google Scholar 

  14. Xu, H., Chen, Z.L., Rajagopal, S., Arunapuram, S.: Solving a practical pickup and delivery problem. Transportation Science 37(3), 347–364 (2003)

    Article  Google Scholar 

  15. Feillet, D., Dejax, P., Gendreau, M.: Traveling Salesman Problems with Profits. Transportation Science 39(2), 188–205 (2005)

    Article  Google Scholar 

  16. Schönberger, J., Kopfer, H., Mattfeld, H.: A combined approach to solve the pickup and delivery selection problem. In: Operations Research Proceedings 2002, pp. 150–155. Springer, Heidelberg (2002)

    Google Scholar 

  17. Powell, W., Snow, W., Cheung, R.: Adaptive labeling algorithms for the dynamic assignment problem. Transportation Science 34(1), 50–66 (2000)

    Article  MATH  Google Scholar 

  18. Campbell, A., Savelsbergh, M.: Efficient insertion heuristics for vehicle routing and scheduling problems. Transportation Science 38(3), 369–378 (2004)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. MIT-Zaragoza International Logistics Program, Zaragoza Logistics Center, Zaragoza, Spain

    Asvin Goel

  2. Applied Telematics/e-Business Group, Department of Computer Science, University of Leipzig, Leipzig, Germany

    Asvin Goel

Authors
  1. Asvin Goel
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Editor information

Editors and Affiliations

  1. ALBCOM Research Group, Universitat Politècnica de Catalunya, Omega 112, Campus Nord, Jordi Girona 1-3, 08034, Barcelona, Spain

    Christian Blum

  2. LION Research Group, Università degli Studi di Trento, Via Sommarive, 14, 38123, Povo (Trento), Italy

    Roberto Battiti

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Goel, A. (2010). A Column Generation Heuristic for the General Vehicle Routing Problem. In: Blum, C., Battiti, R. (eds) Learning and Intelligent Optimization. LION 2010. Lecture Notes in Computer Science, vol 6073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13800-3_1

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  • DOI: https://doi.org/10.1007/978-3-642-13800-3_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13799-0

  • Online ISBN: 978-3-642-13800-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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