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European Conference on Evolutionary Computation in Combinatorial Optimization

EvoCOP 2017: Evolutionary Computation in Combinatorial Optimization pp 124–140Cite as

LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10197))

Abstract

The pickup and delivery problem with time windows (PDPTW) is an NP-hard discrete optimization problem of serving transportation requests using a fleet of homogeneous trucks. Its main objective is to minimize the number of vehicles, and the secondary objective is to minimize the distance traveled during the service. In this paper, we propose the longest common subsequence based selective route exchange crossover (LCS-SREX), and apply this operator in the memetic algorithm (MA) for the PDPTW. Also, we suggest the new solution representation which helps handle the crossover efficiently. Extensive experimental study performed on the benchmark set showed that using LCS-SREX leads to very high-quality feasible solutions. The analysis is backed with the statistical tests to verify the importance of the elaborated results. Finally, we report one new world’s best routing schedule found using a parallel version of the MA exploiting LCS-SREX.

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Notes

  1. 1.

    See: http://www.sintef.no/projectweb/top/pdptw/li--lim-benchmark/.

  2. 2.

    The supplementary material is available at: http://sun.aei.polsl.pl/~jnalepa/EvoCOP2017/evocop2017_supplement.zip.

References

  1. Nalepa, J., Blocho, M.: Adaptive memetic algorithm for minimizing distance in the vehicle routing problem with time windows. Soft Comput. 20(6), 2309–2327 (2016)

    Article  Google Scholar 

  2. Nagata, Y., Kobayashi, S.: Guided ejection search for the pickup and delivery problem with time windows. In: Cowling, P., Merz, P. (eds.) EvoCOP 2010. LNCS, vol. 6022, pp. 202–213. Springer, Heidelberg (2010). doi:10.1007/978-3-642-12139-5_18

    Chapter  Google Scholar 

  3. Kececi, B., Altiparmak, F., Kara, I.: A hybrid constructive mat-heuristic algorithm for the heterogeneous vehicle routing problem with simultaneous pick-up and delivery. In: Chicano, F., Hu, B., García-Sánchez, P. (eds.) EvoCOP 2016. LNCS, vol. 9595, pp. 1–17. Springer, Heidelberg (2016). doi:10.1007/978-3-319-30698-8_1

    Chapter  Google Scholar 

  4. Grandinetti, L., Guerriero, F., Pezzella, F., Pisacane, O.: The multi-objective multi-vehicle pickup and delivery problem with time windows. Soc. Behav. Sci. 111, 203–212 (2014)

    Article  Google Scholar 

  5. Nanry, W.P., Barnes, J.W.: Solving the pickup and delivery problem with time windows using reactive tabu search. Transp. Res. 34(2), 107–121 (2000)

    Article  Google Scholar 

  6. Cordeau, J.F., Laporte, G., Ropke, S.: Recent models and algorithms for one-to-one pickup and delivery problems. In: Golden, B., Raghavan, S., Wasil, E. (eds.) The Vehicle Routing Problem: Latest Advances and New Challenges, pp. 327–357. Springer, Boston (2008)

    Chapter  Google Scholar 

  7. Baldacci, R., Mingozzi, A., Roberti, R.: Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints. Eur. J. Oper. Res. 218(1), 1–6 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  8. Bettinelli, A., Ceselli, A., Righini, G.: A branch-and-price algorithm for the multi-depot heterogeneous-fleet pickup and delivery problem with soft time windows. Math. Program. Comput. 6(2), 171–197 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  9. Baldacci, R., Bartolini, E., Mingozzi, A.: An exact algorithm for the pickup and delivery problem with time windows. Oper. Res. 59(2), 414–426 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  10. Lu, Q., Dessouky, M.M.: A new insertion-based construction heuristic for solving the pickup and delivery problem with time windows. Eur. J. Oper. Res. 175(2), 672–687 (2006)

    Article  MATH  Google Scholar 

  11. Zhou, C., Tan, Y., Liao, L., Liu, Y.: Solving multi-vehicle pickup and delivery with time widows by new construction heuristic. In: Procedings of CISDA, pp. 1035–1042 (2006)

    Google Scholar 

  12. Parragh, S.N., Doerner, K.F., Hartl, R.F.: A survey on pickup and delivery problems. J. fur Betriebswirtschaft 58(1), 21–51 (2008)

    Article  Google Scholar 

  13. Ropke, S., Pisinger, D.: An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows. Transp. Sci. 40(4), 455–472 (2006)

    Article  Google Scholar 

  14. Nalepa, J., Blocho, M.: Enhanced guided ejection search for the pickup and delivery problem with time windows. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, T.-P. (eds.) ACIIDS 2016. LNCS (LNAI), vol. 9621, pp. 388–398. Springer, Heidelberg (2016). doi:10.1007/978-3-662-49381-6_37

    Chapter  Google Scholar 

  15. Pankratz, G.: A grouping genetic algorithm for the pickup and delivery problem with time windows. OR Spectr. 27(1), 21–41 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  16. Nagata, Y., Kobayashi, S.: A memetic algorithm for the pickup and delivery problem with time windows using selective route exchange crossover. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds.) PPSN 2010. LNCS, vol. 6238, pp. 536–545. Springer, Heidelberg (2010). doi:10.1007/978-3-642-15844-5_54

    Google Scholar 

  17. Bent, R., Hentenryck, P.V.: A two-stage hybrid algorithm for pickup and delivery routing problems with time windows. Comput. Oper. Res. 33(4), 875–893 (2006)

    Article  MATH  Google Scholar 

  18. Kalina, P., Vokrinek, J.: Parallel solver for vehicle routing and pickup and delivery problems with time windows based on agent negotiation. In: Proceedings of IEEE SMC, pp. 1558–1563 (2012)

    Google Scholar 

  19. Nalepa, J., Blocho, M.: Co-operation in the parallel memetic algorithm. Int. J. Parallel Program. 43(5), 812–839 (2014)

    Article  Google Scholar 

  20. Blocho, M., Nalepa, J.: A parallel algorithm for minimizing the fleet size in the pickup and delivery problem with time windows. In: Proceedings of 22nd European MPI Users’ Group Meeting, EuroMPI 2015, pp. 15:1–15:2. ACM, New York (2015)

    Google Scholar 

  21. Nalepa, J., Blocho, M.: A parallel algorithm with the search space partition for the pickup and delivery with time windows. In: Proceedings of 3PGCIC, pp. 92–99 (2015)

    Google Scholar 

  22. Cherkesly, M., Desaulniers, G., Laporte, G.: A population-based metaheuristic for the pickup and delivery problem with time windows and LIFO loading. Comput. Oper. Res. 62, 23–35 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  23. Szudzik, M.: An Elegant Pairing Function. Wolfram Research, Champaign (2006). pp. 1–12

    Google Scholar 

  24. Demšar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7, 1–30 (2006)

    MathSciNet  MATH  Google Scholar 

  25. Krawczyk, B., Woźniak, M., Herrera, F.: On the usefulness of one-class classifier ensembles for decomposition of multi-class problems. Pattern Recogn. 48(12), 3969–3982 (2015)

    Article  Google Scholar 

  26. Trajdos, P., Kurzynski, M.: A dynamic model of classifier competence based on the local fuzzy confusion matrix and the random reference classifier. Appl. Math. Comput. Sci. 26(1), 175 (2016)

    MathSciNet  MATH  Google Scholar 

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Acknowledgments

This research was supported by the National Science Centre under research Grant No. DEC-2013/09/N/ST6/03461, and performed using the Intel CPU and Xeon Phi platforms provided by the MICLAB project No. POIG.02.03.00.24-093/13.

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Authors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    Miroslaw Blocho & Jakub Nalepa

Authors
  1. Miroslaw Blocho
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  2. Jakub Nalepa
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Correspondence to Jakub Nalepa .

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Editors and Affiliations

  1. Austrian Institute of Technology, Vienna, Austria

    Bin Hu

  2. University of Manchester, Manchester, United Kingdom

    Manuel López-Ibáñez

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Blocho, M., Nalepa, J. (2017). LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows. In: Hu, B., López-Ibáñez, M. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2017. Lecture Notes in Computer Science(), vol 10197. Springer, Cham. https://doi.org/10.1007/978-3-319-55453-2_9

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  • DOI: https://doi.org/10.1007/978-3-319-55453-2_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55452-5

  • Online ISBN: 978-3-319-55453-2

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