Skip to main content

Speeding Up Logic-Based Benders’ Decomposition by a Metaheuristic for a Bi-Level Capacitated Vehicle Routing Problem

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8457))

Abstract

Benders’ Decomposition (BD) is a prominent technique for tackling large mixed integer programming problems having a certain structure by iteratively solving a series of smaller master and subproblem instances. We apply a generalization of this technique called Logic-Based BD, which does not restrict the subproblems to have continuous variables only, to a bi-level vehicle routing problem originating in the timely distribution of printed newspapers to subscribers. When solving all master and subproblem instances exactly by CPLEX, it turns out that the scalability of the approach is quite limited. The situation can be dramatically improved when using a meaningful metaheuristic – in our case a variable neighborhood search – for approximately solving either only the subproblems or both, the master as well as the subproblem instances. More generally, it is shown that Logic-Based BD can be a highly promising framework also for hybrid metaheuristics.

This work is supported by the Austrian Ministry for Transport, Innovation and Technology, the Ferderal State of Salzburg, Austria, and the Austrian Science Fund (FWF) under grant P24660.

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

Buying options

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Benders, J.F.: Partitioning procedures for solving mixed-variables programming problems. Numerische Mathematik 4, 238–252 (1962)

    Article  MATH  MathSciNet  Google Scholar 

  2. Geoffrion, A.M.: Generalized Benders decomposition. Journal of Optimization Theory and Applications 10(4), 237–260 (1972)

    Article  MATH  MathSciNet  Google Scholar 

  3. Hooker, J.N., Ottosson, G.: Logic-based benders decomposition. Mathematical Programming 96, 33–60 (2003)

    MATH  MathSciNet  Google Scholar 

  4. Hooker, J.N.: Planning and scheduling by logic-based Benders decomposition. Operations Research 55(3), 588–602 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  5. Poojari, C.A., Beasley, J.E.: Improving Benders decomposition using a genetic algorithm. European Journal of Operational Research 199(1), 89–97 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  6. Lai, M.C., Sohn, H.S., Tseng, T.L., Chiang, C.: A hybrid algorithm for capacitated plant location problem. Expert Systems with Applications 37(12), 8599–8605 (2010)

    Article  Google Scholar 

  7. Lai, M.C., Sohn, H.S.: Using a genetic algorithm to solve the Benders master problem for capacitated plant location. In: Gao, S. (ed.) Bio-Inspired Computational Algorithms and Their Applications, pp. 405–420. InTech (2012)

    Google Scholar 

  8. Lai, M.C., Sohn, H.S., Tseng, T.L., Bricker, D.L.: A hybrid Benders/genetic algorithm for vehicle routing and scheduling problem. International Journal of Industrial Engineering 19(1), 33–46 (2012)

    Google Scholar 

  9. Rei, W., Cordeau, J.F., Gendreau, M., Soriano, P.: Accelerating Benders decomposition by local branching. INFORMS Journal on Computing 21(2), 333–345 (2008)

    Article  MathSciNet  Google Scholar 

  10. Zakeri, G., Philpott, A.B., Ryan, D.M.: Inexact cuts in Benders decomposition. SIAM Journal on Optimization 10(3), 643–657 (1999)

    Article  MathSciNet  Google Scholar 

  11. Perboli, G., Tadei, R., Vigo, D.: The two-echelon capacitated vehicle routing problem: Models and math-based heuristics. Transportation Science 45(3), 364–380 (2011)

    Article  Google Scholar 

  12. Hemmelmayr, V.C., Cordeau, J.F., Crainic, T.G.: An adaptive large neighborhood search heuristic for two-echelon vehicle routing problems arising in city logistics. Computers and Operations Research 39(12), 3215–3228 (2012)

    Article  MathSciNet  Google Scholar 

  13. Schwengerer, M., Pirkwieser, S., Raidl, G.R.: A variable neighborhood search approach for the two-echelon location-routing problem. In: Hao, J.-K., Middendorf, M. (eds.) EvoCOP 2012. LNCS, vol. 7245, pp. 13–24. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  14. Crainic, T.G., Mancini, S., Perboli, G., Tadei, R.: Multi-start heuristics for the two-echelon vehicle routing problem. In: Hao, J.-K. (ed.) EvoCOP 2011. LNCS, vol. 6622, pp. 179–190. Springer, Heidelberg (2011)

    Google Scholar 

  15. Jacobsen, S.K., Madsen, O.B.G.: A comparative study of heuristics for a two-level routing-location problem. European Journal of Operational Research 5(6), 378–387 (1980)

    Article  MATH  Google Scholar 

  16. Boccia, M., Crainic, T., Sforza, A., Sterle, C.: A metaheuristic for a two echelon location-routing problem. In: Festa, P. (ed.) SEA 2010. LNCS, vol. 6049, pp. 288–301. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  17. Boccia, M., Crainic, T.G., Sforza, A., Sterle, C.: Location-routing models for designing a two-echelon freight distribution system. Technical Report CIRRELT-2011-06, University of Montreal (2011)

    Google Scholar 

  18. Fisher, M.L., Jaikumar, R.: A generalized assignment heuristic for vehicle routing. Networks 11(2), 109–124 (1981)

    Article  MathSciNet  Google Scholar 

  19. Boschetti, M., Maniezzo, V.: Benders decomposition, Lagrangian relaxation and metaheuristic design. Journal of Heuristics 15, 283–312 (2009)

    Article  MATH  Google Scholar 

  20. Yaman, H.: Formulations and valid inequalities for the heterogeneous vehicle routing problem. Mathematical Programming 106(2), 365–390 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  21. Pirkwieser, S., Raidl, G.R.: A variable neighborhood search for the periodic vehicle routing problem with time windows. In: Prodhon, C., et al. (eds.) Proceedings of the 9th EU/MEeting on Metaheuristics for Logistics and Vehicle Routing, Troyes, France (2008)

    Google Scholar 

  22. Clarke, G., Wright, J.W.: Scheduling of vehicles from a central depot to a number of delivery points. Operations Research 12(4), 568–581 (1964)

    Article  Google Scholar 

  23. Mladenović, N., Hansen, P.: Variable neighborhood search. Computers and Operations Research 24(11), 1097–1100 (1997)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Raidl, G.R., Baumhauer, T., Hu, B. (2014). Speeding Up Logic-Based Benders’ Decomposition by a Metaheuristic for a Bi-Level Capacitated Vehicle Routing Problem. In: Blesa, M.J., Blum, C., Voß, S. (eds) Hybrid Metaheuristics. HM 2014. Lecture Notes in Computer Science, vol 8457. Springer, Cham. https://doi.org/10.1007/978-3-319-07644-7_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-07644-7_14

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07643-0

  • Online ISBN: 978-3-319-07644-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics