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GRASP Method for Vehicle Routing with Delivery Place Selection

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 11516)

Abstract

In this paper we present a greedy randomized adaptive search procedure (GRASP) for solving a vehicle routing problem (VRP) for package delivery with delivery place selection. The problem can be solved by stepwise optimization, i.e., first selecting delivery sites and then defining routes based on that selection. Alternatively, it can be solved by jointly optimizing delivery site selection and routing. We investigate the effects of stepwise optimization in comparison to joint optimization. The evaluation results show that our proposed stepwise approach, while expectedly producing longer routes than joint approach (by \(4\%\) on average), can provide a solution \(1000\times \) faster than the previous benchmark approach. The proposed procedure is therefore well suited for the dynamic environment of package delivery which is widespread in modern cities as a consequence of e-commerce.

Keywords

  • Greedy randomized adaptive search procedure
  • Vehicle routing problem
  • Package delivery

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References

  1. Schittekat, P., Kinable, J., Sörensen, K., Sevaux, M., Spieksma, F., Springael, J.: A metaheuristic for the school bus routing problem with bus stop selection. Eur. J. Oper. Res. 229(2), 518–528 (2013)

    CrossRef  Google Scholar 

  2. Toth, P., Vigo, D.: An overview of vehicle routing problems, pp. 1–26 (2001)

    Google Scholar 

  3. Archetti, C., Speranza, M.G.: A survey on matheuristics for routing problems. EURO J. Comput. Optim. 2(4), 223–246 (2014)

    CrossRef  Google Scholar 

  4. Laporte, G., Nobert, Y., Taillefer, S.: Solving a family of multi-depot vehicle routing and location-routing problems. Transp. Sci. 22(3), 161–172 (1988)

    MathSciNet  CrossRef  Google Scholar 

  5. Feo, T.A., Resende, M.G.C.: Greedy randomized adaptive search procedures. J. Glob. Optim. 6(2), 109–133 (1995). https://doi.org/10.1007/BF01096763

    MathSciNet  CrossRef  MATH  Google Scholar 

  6. Park, J., Kim, B.I.: The school bus routing problem: a review. Eur. J. Oper. Res. 202(2), 311–319 (2010)

    MathSciNet  CrossRef  Google Scholar 

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Acknowledgment

This research has been partly supported by the European Regional Development Fund under the grant KK.01.1.1.01.0009 (DATACROSS).

The authors acknowledge the support of the Croatian Science Foundation through the Reliable Composite Applications Based on Web Services (IP-01-2018-6423) research project.

The Titan X Pascal used for this research was donated by the NVIDIA Corporation.

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Correspondence to Petar Afric .

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Afric, P. et al. (2019). GRASP Method for Vehicle Routing with Delivery Place Selection. In: Wang, D., Zhang, LJ. (eds) Artificial Intelligence and Mobile Services – AIMS 2019. AIMS 2019. Lecture Notes in Computer Science(), vol 11516. Springer, Cham. https://doi.org/10.1007/978-3-030-23367-9_6

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  • DOI: https://doi.org/10.1007/978-3-030-23367-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-23366-2

  • Online ISBN: 978-3-030-23367-9

  • eBook Packages: Computer ScienceComputer Science (R0)