Skip to main content

Multi-objective Heterogeneous Capacitated Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery for Urban Last Mile Logistics

  • Conference paper
Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Volume 1

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 1))

Abstract

The Urban Last Mile Logistics (LML) is known to be the most expensive, least efficient and most polluting section of the supply chain. To that extent, a multi-objective heterogeneous capacitated vehicle routing problem with time windows and simultaneous pickup and delivery (MoHCVRPTWSPD) is formulated and solved to cater to this section of the supply chain. The proposed model is solved through two proposed methods that are based on exact methods. A small benchmark was adopted from the current literature to test the proposed methods and computational results are reported. Based on the computational results, a number of insights into the MoHCVRP-TWSPD problem are provided.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dantzig, G.B., Ramser, J.H.: The truck dispatching problem. Management Science 6(1), 80–91 (1959)

    Article  MATH  MathSciNet  Google Scholar 

  2. Angelelli, E., Mansini, R.: The vehicle routing problem with time windows and simultaneous pick-up and delivery. In: Quantitative Approaches to Distribution Logistics and Supply Chain Management, pp. 249–267. Springer (2002)

    Google Scholar 

  3. Chang, M.-S., Chen, S., Hsueh, C.-F.: Real-time vehicle routing problem with time windows and simultaneous delivery/pickup demands. Journal of the Eastern Asia Society for Transportation Studies 5, 2273–2286 (2003)

    Google Scholar 

  4. Gutiérrez-Jarpa, G., et al.: A branch-and-price algorithm for the vehicle routing prob-lem with deliveries, selective pickups and time windows. European Journal of Operational Research 206(2), 341–349 (2010)

    Article  MATH  Google Scholar 

  5. Mingyong, L., Erbao, C.: An improved differential evolution algorithm for vehicle routing problem with simultaneous pickups and deliveries and time windows. Engineering Applications of Artificial Intelligence 23(2), 188–195 (2010)

    Article  Google Scholar 

  6. Wang, H.-F., Chen, Y.-Y.: A genetic algorithm for the simultaneous delivery and pickup problems with time window. Computers & Industrial Engineering 62(1), 84–95 (2012)

    Article  Google Scholar 

  7. Desrosiers, J., et al.: Time constrained routing and scheduling. In: Handbooks in Operations Research and Management Science, vol. 8, pp. 35–139 (1995)

    Google Scholar 

  8. Solomon, M.M.: Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research 35(2), 254–265 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  9. Gélinas, S., et al.: A new branching strategy for time constrained routing problems with application to backhauling. Annals of Operations Research 61(1), 91–109 (1995)

    Article  MATH  Google Scholar 

  10. Bektaş, T., Laporte, G.: The Pollution-Routing Problem. Transportation Research Part B: Methodological 45(8), 1232–1250 (2011)

    Article  Google Scholar 

  11. Lin, C., et al.: Survey of Green Vehicle Routing Problem: Past and future trends. Expert Systems with Applications 41(4), 1118–1138 (2014)

    Article  Google Scholar 

  12. Jozefowiez, N., Semet, F., Talbi, E.-G.: Multi-objective vehicle routing problems. European Journal of Operational Research 189(2), 293–309 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  13. Sutcliffe, C., Boardman, J.: Optimal solution of a vehicle-routeing problem: transporting mentally handicapped adults to an adult training centre. Journal of the Operational Research Society, 61–67 (1990)

    Google Scholar 

  14. Hong, S.-C., Park, Y.-B.: A heuristic for bi-objective vehicle routing with time window constraints. International Journal of Production Economics 62(3), 249–258 (1999)

    Article  MathSciNet  Google Scholar 

  15. Sessomboon, W., et al.: A study on multi-objective vehicle routing problem considering customer satisfaction with due-time (the creation of Pareto optimal solutions by hybrid genetic algorithm). Transaction of the Japan Society of Mechanical Engineers (1998)

    Google Scholar 

  16. Murata, T., Itai, R.: Local search in two-fold EMO algorithm to enhance solution similarity for multi-objective vehicle routing problems. In: Obayashi, S., Deb, K., Poloni, C., Hiroyasu, T., Murata, T. (eds.) EMO 2007. LNCS, vol. 4403, pp. 201–215. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  17. Geiger, M.J.: Genetic algorithms for multiple objective vehicle routing. arXiv preprint arXiv:0809.0416 (2008)

    Google Scholar 

  18. Giannikos, I.: A multiobjective programming model for locating treatment sites and routing hazardous wastes. European Journal of Operational Research 104(2), 333–342 (1998)

    Article  MATH  Google Scholar 

  19. Bowerman, R., Hall, B., Calamai, P.: A multi-objective optimization approach to urban school bus routing: Formulation and solution method. Transportation Research Part A: Policy and Practice 29(2), 107–123 (1995)

    Google Scholar 

  20. El-Sherbeny, N.: Resolution of a vehicle routing problem with multi-objective simulated annealing method. Faculté Polytechnique de Mons (2001)

    Google Scholar 

  21. Tavakkoli-Moghaddam, R., Safaei, N., Gholipour, Y.: A hybrid simulated annealing for capacitated vehicle routing problems with the independent route length. Applied Mathematics and Computation 176(2), 445–454 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  22. Moura, A.: A multi-objective genetic algorithm for the vehicle routing with time windows and loading problem. In: Intelligent Decision Support, pp. 187–201. Springer (2008)

    Google Scholar 

  23. Cordeau, J.-F., et al.: VRP with time windows. The Vehicle Routing Problem 9, 157–193 (2002)

    Article  MathSciNet  Google Scholar 

  24. Hickman, J., et al.: Methodology for calculating transport emissions and energy consumption (1999)

    Google Scholar 

  25. Bisschop, J.: AIMMS-optimization modeling. Lulu. com (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chen Kim Heng .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Heng, C.K., Zhang, A.N., Tan, P.S., Ong, YS. (2015). Multi-objective Heterogeneous Capacitated Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery for Urban Last Mile Logistics. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, K. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Volume 1. Proceedings in Adaptation, Learning and Optimization, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-13359-1_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-13359-1_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13358-4

  • Online ISBN: 978-3-319-13359-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics