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Approximation Scheme for the Capacitated Vehicle Routing Problem with Time Windows and Non-uniform Demand

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Abstract

The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is the well-known combinatorial optimization problem having numerous valuable applications in operations research. Unlike the classic CVRP (without time windows constraints), approximation algorithms with theoretical guarantees for the CVRPTW are still developed much less, even for the Euclidean plane. In this paper, perhaps for the first time, we propose an approximation scheme for the planar CVRPTW with non-uniform splittable demand combining the well-known instance decomposition framework by A. Adamaszek et al. and Quasi-Polynomial Time Approximation Scheme (QPTAS) by L. Song et al. Actually, for any \(\varepsilon \in (0,1)\) the scheme proposed finds a \((1+\varepsilon )\)-approximate solution of the problem in polynomial time provided the capacity q and the number p of time windows does not exceed \(2^{\log ^\delta n}\) for some \(\delta =O(\varepsilon )\). For any fixed p and q the scheme is Efficient Polynomial Time Approximation Scheme (EPTAS) with subquadratic time complexity.

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Notes

  1. 1.

    Without loss of generality, we can can assume that \(d(y)=0\), for the depot y.

References

  1. Adamaszek, A., Czumaj, A., Lingas, A.: PTAS for k-tour cover problem on the plane rof moderately large values of \(k\). Int. J. Found. Comput. Sci. 21(06), 893–904 (2010). https://doi.org/10.1142/S0129054110007623

    Article  MATH  Google Scholar 

  2. Arora, S.: Polynomial Time Approximation Schemes for Euclidean Traveling Salesman and other geometric problems. J. ACM 45, 753–782 (1998)

    Article  MathSciNet  Google Scholar 

  3. Asano, T., Katoh, N., Tamaki, H., Tokuyama, T.: Covering points in the plane by k-tours: towards a polynomial time approximation scheme for general k. In: Proceedings of the Twenty-Ninth Annual ACM Symposium on Theory of Computing, STOC 1997, pp. 275–283. ACM, New York (1997). https://doi.org/10.1145/258533.258602

  4. Becker, A., Klein, P.N., Saulpic, D.: A quasi-polynomial-time approximation scheme for vehicle routing on planar and bounded-genus graphs. In: Pruhs, K., Sohler, C. (eds.) 25th Annual European Symposium on Algorithms, ESA 2017, Vienna, Austria, 4–6 September 2017. LIPIcs, vol. 87, pp. 12:1–12:15. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik (2017). https://doi.org/10.4230/LIPIcs.ESA.2017.12. http://www.dagstuhl.de/dagpub/978-3-95977-049-1

  5. Becker, A., Klein, P.N., Saulpic, D.: Polynomial-time approximation schemes for k-center, k-median, and capacitated vehicle routing in bounded highway dimension. In: Azar, Y., Bast, H., Herman, G. (eds.) 26th Annual European Symposium on Algorithms, ESA 2018, Helsinki, Finland, 20–22 August 2018. LIPIcs, vol. 112, pp. 8:1–8:15. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik (2018). https://doi.org/10.4230/LIPIcs.ESA.2018.8. http://www.dagstuhl.de/dagpub/978-3-95977-081-1

  6. Blocho, M., Czech, Z.: A parallel memetic algorithm for the vehicle routing problem with time windows. In: 2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, pp. 144–151 (2013). https://doi.org/10.1109/3PGCIC.2013.28

  7. Cassettari, L., Demartini, M., Mosca, R., Revetria, R., Tonelli, F.: A multi-stage algorithm for a capacitated vehicle routing problem with time constraints. Algorithms 11(5) (2018). https://doi.org/10.3390/a11050069. http://www.mdpi.com/1999-4893/11/5/69

    Article  MathSciNet  Google Scholar 

  8. Chen, X., Kong, Y., Dang, L., Hou, Y., Ye, X.: Exact and metaheuristic approaches for a bi-objective school bus scheduling problem. PLOS ONE 10(7), 1–20 (2015). https://doi.org/10.1371/journal.pone.0132600

    Article  Google Scholar 

  9. Dantzig, G., Ramser, J.: The truck dispatching problem. Manag. Sci. 6, 80–91 (1959)

    Article  MathSciNet  Google Scholar 

  10. Das, A., Mathieu, C.: A quasipolynomial time approximation scheme for Euclidean capacitated vehicle routing. Algorithmica 73, 115–142 (2015). https://doi.org/10.1007/s00453-014-9906-4

    Article  MathSciNet  MATH  Google Scholar 

  11. Gschwind, T., Irnich, S.: Effective handling of dynamic time windows and its application to solving the dial-a-ride problem. Transp. Sci. 49(2), 335–354 (2015)

    Article  Google Scholar 

  12. Haimovich, M., Rinnooy Kan, A.H.G.: Bounds and heuristics for capacitated routing problems. Math. Oper. Res. 10(4), 527–542 (1985). https://doi.org/10.1287/moor.10.4.527

    Article  MathSciNet  MATH  Google Scholar 

  13. Hashimoto, H., Yagiura, M.: A path relinking approach with an adaptive mechanism to control parameters for the vehicle routing problem with time windows. In: van Hemert, J., Cotta, C. (eds.) EvoCOP 2008. LNCS, vol. 4972, pp. 254–265. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-78604-7_22

    Chapter  Google Scholar 

  14. Khachai, M.Y., Dubinin, R.D.: Approximability of the vehicle routing problem in finite-dimensional Euclidean spaces. Proc. Steklov Inst. Math. 297(1), 117–128 (2017). https://doi.org/10.1134/S0081543817050133

    Article  MathSciNet  MATH  Google Scholar 

  15. Khachai, M., Ogorodnikov, Y.: Polynomial time approximation scheme for the capacitated vehicle routing problem with time windows. Trudy instituta matematiki i mekhaniki UrO RAN 24(3), 233–246 (2018). https://doi.org/10.21538/0134-4889-2018-24-3-233-246

    Article  Google Scholar 

  16. Khachay, M., Ogorodnikov, Y.: Efficient PTAS for the Euclidean CVRP with time windows. In: van der Aalst, W.M.P., et al. (eds.) AIST 2018. LNCS, vol. 11179, pp. 318–328. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-11027-7_30

    Chapter  Google Scholar 

  17. Khachay, M., Ogorodnikov, Y.: Improved polynomial time approximation scheme for capacitated vehicle routing problem with time windows. In: Evtushenko, Y., Jaćimović, M., Khachay, M., Kochetov, Y., Malkova, V., Posypkin, M. (eds.) OPTIMA 2018. CCIS, vol. 974, pp. 155–169. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-10934-9_12

    Chapter  Google Scholar 

  18. Khachay, M., Dubinin, R.: PTAS for the Euclidean capacitated vehicle routing problem in \(R^d\). In: Kochetov, Y., Khachay, M., Beresnev, V., Nurminski, E., Pardalos, P. (eds.) DOOR 2016. LNCS, vol. 9869, pp. 193–205. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-44914-2_16

    Chapter  Google Scholar 

  19. Khachay, M., Zaytseva, H.: Polynomial time approximation scheme for single-depot Euclidean capacitated vehicle routing problem. In: Lu, Z., Kim, D., Wu, W., Li, W., Du, D.-Z. (eds.) COCOA 2015. LNCS, vol. 9486, pp. 178–190. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-26626-8_14

    Chapter  Google Scholar 

  20. Kumar, S., Panneerselvam, R.: A survey on the vehicle routing problem and its variants. Intell. Inf. Manag. 4, 66–74 (2012). https://doi.org/10.4236/iim.2012.43010

    Article  Google Scholar 

  21. 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). https://doi.org/10.1007/s00500-015-1642-4

    Article  Google Scholar 

  22. Necula, R., Breaban, M., Raschip, M.: Tackling dynamic vehicle routing problem with time windows by means of ant colony system. In: 2017 IEEE Congress on Evolutionary Computation (CEC), pp. 2480–2487 (2017). https://doi.org/10.1109/CEC.2017.7969606

  23. Pace, S., Turky, A., Moser, I., Aleti, A.: Distributing fibre boards: a practical application of the heterogeneous fleet vehicle routing problem with time windows and three-dimensional loading constraints. Procedia Comput. Sci. 51, 2257–2266 (2015). https://doi.org/10.1016/j.procs.2015.05.382. International Conference on Computational Science, ICCS 2015

    Article  Google Scholar 

  24. Papadimitriou, C.: Euclidean TSP is NP-complete. Theor. Comput. Sci. 4, 237–244 (1977)

    Article  Google Scholar 

  25. Savelsbergh, M., van Woensel, T.: 50th anniversary invited article - city logistics: challenges and opportunities. Transp. Sci. 50(2), 579–590 (2016). https://doi.org/10.1287/trsc.2016.0675

    Article  Google Scholar 

  26. Shen, L., Tao, F., Wang, S.: Multi-depot open vehicle routing problem with time windows based on carbon trading. Int. J. Environ. Res. Public Health 15(9), 2025 (2018). https://doi.org/10.3390/ijerph15092025

    Article  Google Scholar 

  27. Song, L., Huang, H.: The Euclidean vehicle routing problem with multiple depots and time windows. In: Gao, X., Du, H., Han, M. (eds.) COCOA 2017. LNCS, vol. 10628, pp. 449–456. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-71147-8_31

    Chapter  Google Scholar 

  28. Song, L., Huang, H., Du, H.: Approximation schemes for Euclidean vehicle routing problems with time windows. J. Comb. Optim. 32(4), 1217–1231 (2016). https://doi.org/10.1007/s10878-015-9931-5

    Article  MathSciNet  MATH  Google Scholar 

  29. Ting, C.K., Liao, X.L., Huang, Y.H., Liaw, R.T.: Multi-vehicle selective pickup and delivery using metaheuristic algorithms. Inf. Sci. 406–407, 146–169 (2017). https://doi.org/10.1016/j.ins.2017.04.001. http://www.sciencedirect.com/science/article/pii/S0020025517306436

    Article  Google Scholar 

  30. Toth, P., Vigo, D.: Vehicle Routing: Problems, Methods, and Applications. MOS-SIAM Series on Optimization, 2nd edn. SIAM, Philadelphia (2014)

    Book  Google Scholar 

  31. Vidal, T., Crainic, T.G., Gendreau, M., Prins, C.: A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows. Comput. Oper. Res. 40(1), 475–489 (2013). https://doi.org/10.1016/j.cor.2012.07.018

    Article  MathSciNet  MATH  Google Scholar 

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Khachay, M., Ogorodnikov, Y. (2019). Approximation Scheme for the Capacitated Vehicle Routing Problem with Time Windows and Non-uniform Demand. In: Khachay, M., Kochetov, Y., Pardalos, P. (eds) Mathematical Optimization Theory and Operations Research. MOTOR 2019. Lecture Notes in Computer Science(), vol 11548. Springer, Cham. https://doi.org/10.1007/978-3-030-22629-9_22

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  • DOI: https://doi.org/10.1007/978-3-030-22629-9_22

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