Skip to main content
SpringerLink
Log in

An Online Packing Heuristic for the Three-Dimensional Container Loading Problem in Dynamic Environments and the Physical Internet

  • Conference paper
  • First Online:
Applications of Evolutionary Computation (EvoApplications 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10200))

Included in the following conference series:

Abstract

In this paper, we consider the online three-dimensional container loading problem. We develop a novel online packing algorithm to solve the three-dimensional bin packing problem in the online case where items are not known well in advance and they have to be packed in real-time when they arrive. This is relevant in many real-world scenarios such as automated cargo loading in warehouses. This is also relevant in the new logistics model of Physical Internet. The effectiveness of the online packing heuristic is evaluated on a set of generated data. The experimental results show that the algorithm could solve the 3D container loading problems in online fashion and is competitive against other algorithms both in the terms of running time, space utilization and the number of bins.

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

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Bui, L.T., Baker, S., Bender, A., Abbass, H.A., Barlow, M., Saker, R.: A grid-based heuristic for two-dimensional packing problems. In: 2011 IEEE Congress on Evolutionary Computation (CEC), pp. 2329–2336 (2011)

    Google Scholar 

  2. Martello, S., Pisinger, D., Vigo, D.: The three-dimensional bin packing problem. Oper. Res. 48, 256–267 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  3. Anily, S., Bramel, J., Simchi-Levi, D.: Worst-case analysis of heuristics for the bin packing problem with general cost structures. Oper. Res. 42, 287–298 (1994)

    Article  MATH  Google Scholar 

  4. Scheithauer, G.: Algorithms for the container loading problem. In: Gaul, W., et al. (eds.) Operations Research Proceedings 1991, pp. 445–452. Springer, Heidelberg (1992)

    Google Scholar 

  5. Bortfeldt, A., Wäscher, G.: Constraints in container loading–a state-of-the-art review. Eur. J. Oper. Res. 229, 1–20 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  6. Zhao, X., Bennell, J.A., Bektaş, T., Dowsland, K.: A comparative review of 3D container loading algorithms. Int. Trans. Oper. Res. 23, 287–320 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  7. Junqueira, L., Morabito, R., Yamashita, D.S.: Three-dimensional container loading models with cargo stability and load bearing constraints. Comput. Oper. Res. 39, 74–85 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  8. Moon, I., Nguyen, T.V.L.: Container packing problem with balance constraints. OR Spectr. 36, 837–878 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  9. Liu, D.S., Tan, K.C., Huang, S.Y., Goh, C.K., Ho, W.K.: On solving multiobjective bin packing problems using evolutionary particle swarm optimization. Eur. J. Oper. Res. 190, 357–382 (2008)

    Google Scholar 

  10. Montreuil, B.: Toward a Physical Internet: meeting the global logistics sustainability grand challenge. Logistics Res. 3, 71–87 (2011)

    Article  Google Scholar 

  11. ALICE, Global Supply Network Coordination and Collaboration research & innovation roadmap. ALICE - Alliance for Logistics Innovation through Collaboration in Europe (2014)

    Google Scholar 

  12. Nguyen, T.T., Yang, S., Branke, J.: Evolutionary dynamic optimization: a survey of the state of the art. Swarm Evol. Comput. 6, 1–24 (2012)

    Article  Google Scholar 

  13. Berndt, S., Jansen, K., Klein, K.-M.: Fully dynamic bin packing revisited, arXiv preprint arXiv:1411.0960 (2014)

  14. Coffman, J., Edward, G., Garey, M.R., Johnson, D.S.: Dynamic bin packing. SIAM J. Comput. 12, 227–258 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  15. Epstein, L., Levy, M.: Dynamic multi-dimensional bin packing. J. Discrete Algorithms 8, 356–372 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  16. Feng, X., Moon, I., Shin, J.: Hybrid genetic algorithms for the three-dimensional multiple container packing problem. Flex. Serv. Manuf. J. 27, 451–477 (2015)

    Article  Google Scholar 

  17. Li, X., Zhang, K.: A hybrid differential evolution algorithm for multiple container loading problem with heterogeneous containers. Comput. Ind. Eng. 90, 305–313 (2015)

    Article  Google Scholar 

  18. Lodi, A., Martello, S., Vigo, D.: Heuristic algorithms for the three-dimensional bin packing problem. Eur. J. Oper. Res. 141, 410–420 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  19. Martello, S., Pisinger, D., Vigo, D., Boef, E.D., Korst, J.: Algorithm 864: general and robot-packable variants of the three-dimensional bin packing problem. ACM Trans. Math. Softw. (TOMS) 33, 7 (2007)

    Google Scholar 

  20. Baldi, M.M., Crainic, T.G., Perboli, G., Tadei, R.: The generalized bin packing problem. Transp. Res. Part E Logistics Transp. Rev. 48, 1205–1220 (2012)

    Article  MATH  Google Scholar 

  21. Crainic, T.G., Perboli, G., Tadei, R.: Extreme point-based heuristics for three-dimensional bin packing. Informs J. Comput. 20, 368–384 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  22. Parreño, F., Alvarez-Valdés, R., Oliveira, J., Tamarit, J.M.: A hybrid GRASP/VND algorithm for two-and three-dimensional bin packing. Ann. Oper. Res. 179, 203–220 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  23. Gonçalves, J.F., Resende, M.G.: A biased random key genetic algorithm for 2D and 3D bin packing problems. Int. J. Prod. Econ. 145, 500–510 (2013)

    Article  Google Scholar 

  24. Gonçalves, J.F., Resende, M.G.C.: A parallel multi-population biased random-key genetic algorithm for a container loading problem. Comput. Oper. Res. 39, 179–190 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  25. Lai, K., Chan, J.W.: Developing a simulated annealing algorithm for the cutting stock problem. Comput. Ind. Eng. 32, 115–127 (1997)

    Article  Google Scholar 

  26. Christensen, S.G., Rousøe, D.M.: Container loading with multi-drop constraints. Int. Trans. Oper. Res. 16, 727–743 (2009)

    Article  MATH  Google Scholar 

  27. Tiwari, S., Fadel, G., Fenyes, P.: A fast and efficient compact packing algorithm for free-form objects. In: ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pp. 543–552 (2008)

    Google Scholar 

  28. Karabulut, K., İnceoğlu, M.M.: A hybrid genetic algorithm for packing in 3d with deepest bottom left with fill method. In: International Conference on Advances in Information Systems, pp. 441–450 (2004)

    Google Scholar 

  29. Kang, K., Moon, I., Wang, H.: A hybrid genetic algorithm with a new packing strategy for the three-dimensional bin packing problem. Appl. Math. Comput. 219, 1287–1299 (2012)

    MathSciNet  MATH  Google Scholar 

  30. Wang, H., Chen, Y.: A hybrid genetic algorithm for 3d bin packing problems. In: 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), pp. 703–707 (2010)

    Google Scholar 

  31. Wang, R., Nguyen, T.T., Kavakeb, S., Yang, Z., Li, C.: Benchmarking Dynamic Three-Dimensional Bin Packing Problems Using Discrete-Event Simulation. In: Squillero, G., Burelli, P. (eds.) EvoApplications 2016. LNCS, vol. 9598, pp. 266–279. Springer, Heidelberg (2016). doi:10.1007/978-3-319-31153-1_18

    Chapter  Google Scholar 

Download references

Acknowledgement

This work is supported by a Newton Institutional Links grant funded by the UK BEIS via the British Council, a Newton Research Collaborations Programme (3) grant funded by the UK BEIS via the Royal Academy of Engineering, and a Seed-corn project funded by the Chartered Institute of Logistics and Transport.

The authors thank anonymous reviews for their suggestions and contributions and corresponding editor for his/her valuable efforts.

Author information

Authors and Affiliations

  1. Le Quy Don Technical University, Hanoi, Vietnam

    Chi Trung Ha & Lam Thu Bui

  2. Liverpool John Moores University, Liverpool, UK

    Trung Thanh Nguyen & Ran Wang

Authors
  1. Chi Trung Ha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Trung Thanh Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lam Thu Bui
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ran Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Chi Trung Ha , Trung Thanh Nguyen , Lam Thu Bui or Ran Wang .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Ha, C.T., Nguyen, T.T., Bui, L.T., Wang, R. (2017). An Online Packing Heuristic for the Three-Dimensional Container Loading Problem in Dynamic Environments and the Physical Internet. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10200. Springer, Cham. https://doi.org/10.1007/978-3-319-55792-2_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-55792-2_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55791-5

  • Online ISBN: 978-3-319-55792-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation