Skip to main content
Log in

Multiobjective vehicle routing problem with fixed delivery and optional collections

  • Original Paper
  • Published:
Optimization Letters Aims and scope Submit manuscript

Abstract

We present an adaption on the formulation for the vehicle routing problem with fixed delivery and optional collections, in which the simultaneous minimization of route costs and of collection demands not fulfilled is considered. We also propose a multiobjective version of the iterated local search (MOILS). The performance of the MOILS is compared with the \(\epsilon \)-constrained (\(P_{\epsilon }\)) ILS, the NSGA-II and the indicator-based multi-objective local search methods in the solution of 14 problem instances containing between 50 and 199 customers plus the depot. The results indicate that the MOILS outperformed the other approaches, obtaining significantly better average values for coverage, hypervolume and cardinality.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. The algorithm implementations, problem instances, and statistical routines used in the analysis of this experiment are available online at the address http://www.cpdee.ufmg.br/~fcampelo/files/OPTL2012a./.

References

  1. Batista, L.S., Campelo, F., Guimarães, F.G., Ramírez, J.A.: Pareto cone \(\epsilon \)-dominance: improving convergence and diversity in multiobjective evolutionary algorithms. Lect. Notes Comput Sci. (Springer) 6576, 76–90 (2011)

  2. Batista, L.S., Campelo, F., Guimarães, F.G., Ramírez, J.A.: The cone \(\epsilon \)-dominance: an approach for evolutionary multiobjective optimization. Evol. Comput. (submitted)

  3. Basseur, M., Liefooghe, A., Le, K., Burke, E.K.: The efficiency of indicator-based local search for multi-objective combinatorial optimization problems. J. Heuristics 18(2), 263–296 (2011)

    Article  Google Scholar 

  4. Chankong, V., Haimes, Y.Y.: Multiobjective decision making theory and methodology. Elsevier Science, New York (1983)

  5. Czyzak, P., Jaszkiewicz, A.: Pareto simulated annealing: a metaheuristic technique for multiple-objective combinatorial optimization. J. Multi-Crit. Decis. Anal. 3, 83–104 (1998)

    Google Scholar 

  6. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)

    Article  Google Scholar 

  7. Dunn, O.J.: Multiple Comparisons Among Means. J. Am. Stat. Assoc. 56, 52–64 (1961)

    Article  MathSciNet  MATH  Google Scholar 

  8. Fonseca, C.M., Fleming, P.J.: An overview of evolutionary algorithms in multiobjective optimization. Evol. Comput. 3, 1–16 (1995)

    Article  Google Scholar 

  9. Gandibleux, X., Mezdaoui, N., Fréville, A.: A tabu search procedure to solve multiobjective combinatorial optimization problems. In: Caballero, R., Steuer, R. (eds.) Proceedings Volume of MOPGP 96. Springer, Berlin (1996)

  10. Goh, C.K., Ong, Y.S., Tan, K.C.: Multiobjective memetic algorithms. Springer, Berlin (2009)

  11. Gore, A.: Some nonparametric tests and selection procedures for main effects in two-way layouts. Ann. Inst. Stat. Math. 27(1), 487–500 (1973)

    Article  MathSciNet  Google Scholar 

  12. Gendreau, M., Potvin, J.Y., Bräysy, O., Hasle, G., Løkketangen, A.: Metaheuristics for the vehicle routing problem and its extensions: a categorized bibliography. In: Golden, B., Raghavan, S., Wasil, E. (eds.) The Vehicle Routing Problem—Latest Advances and New Challenges. Springer, New York (2008)

    Google Scholar 

  13. Gribkovskaia, I., Laporte, G., Shyshou, A.: The single vehicle routing problem with deliveries and selective pickups. Comput. Oper. Res. 35, 2908–2924 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  14. Gutiérrez-Jarpa, G., Marianov, V., Obreque, C.: A single vehicle routing problem with fixed delivery and optional collections. IIE Trans. 41, 1067–1079 (2009)

    Article  Google Scholar 

  15. Gutiérrez-Jarpa, G., Desaulniers, G., Laporte, G., Marianov, V.: A branch-and-price algorithm for the vehicle routing problem with deliveries, selective pickups and time windows. Eur. J. Oper. Res. 206, 341–349 (2010)

    Article  MATH  Google Scholar 

  16. Hansen, M.P.: Tabu search for multiobjective optimization: MOTS. MCDM Conference (1997)

  17. Hodges, J., Lehmann, E.: Estimation of location based on ranks. Ann. Math. Stat. 34, 598–611 (1963)

    Article  MathSciNet  MATH  Google Scholar 

  18. Jaszkiewicz, A.: Genetic local search for multi-objective combinatorial optimization. Eur. J. Oper. Res. 137(1), 50–71 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  19. Jozefowiez, N., Semet, F., Talbi, E.G.: An evolutionary algorithm for the vehicle routing problem with route balancing. Eur. J. Oper. Res. 195(3), 761–769 (2007)

    Article  Google Scholar 

  20. Jozefowiez, N., Semet, F., Talbi, E.G.: Multi-objective vehicle routing problems. Eur. J. Oper. Res. 189(2), 293–309 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  21. Lee, T.-R., Ueng, J.-H.: A study of vehicle routing problem with load balancing. Int. J. Phys. Distrib. Logist. Manag. 29, 646–648 (1998)

    Article  Google Scholar 

  22. Lourenço H.R., Martin O.C., Stützle T.: Iterated local search. In: Glover F., Kochenberger G.A. (eds.) Handbook of Metaheuristics, pp. 321–353. Kluwer Academic Publishers, Boston (2003)

  23. Montané, F.A.T., Galvão, R.D.: A tabu search algorithm for the vehicle routing problem with simultaneous pick-up and delivery service. Comput. Oper. Res. 33, 595–619 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  24. Montgomery, D.: Design and analysis of experiments, 7th edn. Wiley, New York (2008)

  25. Osman, I.H.: Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem. Ann. Oper. Res. 41, 421–451 (1993)

    Article  MATH  Google Scholar 

  26. Pacheco, J., Martí, R.: Tabu search for a multiobjective routing problem. J. Oper. Res. Soc. 57(1), 29–37 (2006)

    Article  MATH  Google Scholar 

  27. Penna, P., Subramanian, A., Ochi, L.: An iterated local search heuristic for the heterogeneous fleet vehicle routing problem. J. Heuristics (2011). doi:10.1007/s10732-011-9186-y

  28. Ribeiro, R., Lourenco, H.R.: A multi-objective model for a multi-period distribution management problem. In: Metaheuristic International Conference (MIC), 97–101 (2001)

  29. Salhi, S., Nagy, G.: A cluster insertion heuristic for single and multiple depot vehicle routing problems with backhauling. J. Oper. Res. Soc. 50, 1034–1042 (1999)

    MATH  Google Scholar 

  30. Schaffer, J.D.: Multiple objective optimization with vector evaluated genetic algorithms. In: International Conference on Genetic Algorithm and Their Applications (1985)

  31. Serafini, P.: Simulated annealing for multi-objective optimization problems. In: Tzeng, G.H., Wang, H.F., Wen, V.P., Yu, P.L. (eds.) Multiple Criteria Decision Making. Expand and Enrich the Domains of Thinking and Application, pp. 283–292. Springer, Berlin (1994)

  32. Subramanian, A., Drummond, L., Bentes, C., Ochi, L., Farias, R.: A parallel heuristic for the vehicle routing problem with simultaneous pickup and delivery. Comput. Oper. Res. 37(11), 1899–1911 (2010)

    Article  MATH  Google Scholar 

  33. Subramanian, A., Uchoa, E., Pessoa, A.A., Ochi, L.S.: Branch-and-cut with lazy separation for the vehicle routing problem with simultaneous pickup and delivery. Oper. Res. Lett. 39(5), 338–341 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  34. Süral, H., Bookbinder, J.H.: The single-vehicle routing problem with unrestricted backhauls. Networks 41(3), 127–136 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  35. Ulungu, E.L., Teghem, J.: Multi-objective combinatorial optimization problems: a survey. J. Multi-Crit. Decis. Anal. 3, 83–104 (1994)

    Article  MATH  Google Scholar 

  36. Ulungu, E.L., Teghem, J., Fortemps, Ph: Tuyttens: MOSA method: a tool for solving multiobjective combinatorial optimization problems. J. Multi-Crit. Decis. Anal. 8, 221–236 (1999)

    Article  MATH  Google Scholar 

  37. Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C. M., Fonseca, V.G.: Performance assessment of multiobjective optimizers: an analysis and review. IEEE Trans. Evol. Comput. 7, 117–132 (2003)

    Google Scholar 

Download references

Acknowledgments

This work was supported by the following agencies: National Council for Research and Development (CNPq), grants 306910/2006-3 and 472446/2010-0; the Coordination for the Improvement of Higher Education Personnel (CAPES); and the Research Foundation of the State of Minas Gerais (FAPEMIG, Brazil), grants Pronex: TEC 01075/09 and Pronem: CEX APQ-04611-10.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jaime A. Ramírez.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Assis, L.P., Maravilha, A.L., Vivas, A. et al. Multiobjective vehicle routing problem with fixed delivery and optional collections. Optim Lett 7, 1419–1431 (2013). https://doi.org/10.1007/s11590-012-0551-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11590-012-0551-z

Keywords

Navigation