DOI QR코드

DOI QR Code

On the Theoretical Solution and Application to Container Loading Problem using Normal Distribution Based Model

정규 분포 모델을 이용한 화물 적재 문제의 이론적 해법 도출 및 활용

  • Received : 2022.11.16
  • Accepted : 2022.11.21
  • Published : 2022.12.31

Abstract

This paper introduces a container loading problem and proposes a theoretical approach that efficiently solves it. The problem is to determine a proper weight of products loaded on a container that is delivered by third party logistics (3PL) providers. When the company pre-loads products into a container, typically one or two days in advance of its delivery date, various truck weights of 3PL providers and unpredictability of the randomness make it difficult for the company to meet the total weight regulation. Such a randomness is mainly due to physical difference of trucks, fuel level, and personalized equipment/belongings, etc. This paper provides a theoretical methodology that uses historical shipping data to deal with the randomness. The problem is formulated as a stochastic optimization where the truck randomness is reflected by a theoretical distribution. The data analytics solution of the problem is derived, which can be easily applied in practice. Experiments using practical data reveal that the suggested approach results in a significant cost reduction, compared to a simple average heuristic method. This study provides new aspects of the container loading problem and the efficient solving approach, which can be widely applied in diverse industries using 3PL providers.

Keywords

Acknowledgement

This research was supported by the Yonsei University Research Fund of 2022 (2022-22-0292) and 2022 (2022-22-0076).

References

  1. Aguezzoul, A., Third-party logistics selection problem: A literature review on criteria and methods, Omega, 2014, Vol. 49, pp. 69-78. https://doi.org/10.1016/j.omega.2014.05.009
  2. Akbari, M., Logistics outsourcing: A structured literature review, Benchmarking: An International Journal, 2018.
  3. Bae, M. J., Choi, S. K., and Kim, H. S., ThreeDimensional Container Packing Problem with Freight Priority, Journal of Navigation and Port Research, 2004, Vol. 28, No. 6, pp. 531-539. https://doi.org/10.5394/KINPR.2004.28.6.531
  4. Borgi, T., Nesrine, Z., and Mourad, A., Big data for transport and logistics: A review, 2017 International Conference on Advanced Systems and Electric Technologies (IC_ASET), IEEE, 2017.
  5. Bortfeldt, A. and Gerhard, W. Constraints in container loading- a state-of-the-art review, European Journal of Operational Research, 2013, Vol. 229, No. 1, pp. 1-20. https://doi.org/10.1016/j.ejor.2012.12.006
  6. Chan, F.T.S., Bhagwat, R., Kumar, N., Tiwari, M.K., and Lam, P., Development of a decision support system for air-cargo pallets loading problem: A case study, Expert Systems with Applications, 2006, Vol. 31, No. 3, pp. 472-485. https://doi.org/10.1016/j.eswa.2005.09.057
  7. Egeblad, J. Egeblad, J., Garavelli, C., Lisi, S., and Pisinger, D., Heuristics for container loading of furniture, European Journal of Operational Research, 2010 Vol. 200, No. 3, pp. 881-892. https://doi.org/10.1016/j.ejor.2009.01.048
  8. Hong, D., The method of container loading scheduling through hierarchical clustering, Journal of The Korea Society of Computer and Information, 2005, Vol. 10, No. 1, pp. 201-208.
  9. Iori, M. and Silvano, M., Routing problems with loading constraints, Top, 2010, Vol. 18, No. 1, pp. 4-27. https://doi.org/10.1007/s11750-010-0144-x
  10. Kim, Y.M. and Lee, J.H., A study of the layout of boxes to the cargo loading problems, Journal of Korea Safety Management & Science, 2006, Vol. 8, No. 3, pp. 143-157.
  11. Marasco, A., Third-party logistics: A literature review, International Journal of Production Economics, Vol. 113, No. 1, pp. 127-147. https://doi.org/10.1016/j.ijpe.2007.05.017
  12. Menner, M., Want a Better Supply Chain, Here Are 4, 2015.
  13. Premkumar, P., Saji, G., and Arqum, M., Trends in third party logistics-the past, the present & the future, International Journal of Logistics Research and Applications, 2008, Vol. 24, No. 6, 2021, pp. 551-580. https://doi.org/10.1080/13675567.2020.1782863
  14. Ryu, K. and Park, J., Quantification of loading efficiency of various type loads in a 20 FT container with post selecting process after applying conventional loading algorithms, Journal of Korea Multimedia Society, 2018, Vol. 21, No. 4, pp. 513-526. https://doi.org/10.9717/KMMS.2018.21.4.513
  15. Ton, Z. and Wheelwright, S. C., Exel Plc: Supply Chain Management at Haus Mart. Harvard Business School, 2005.
  16. Vasiliauskas, A. V. and Jakubauskas, G., Principle and benefits of third party logistics approach when managing logistics supply chain, Transport, 2007, Vol. 22, No. 2, pp. 68-72. https://doi.org/10.3846/16484142.2007.9638101
  17. Yeo, G.T., Soak, S., and Lee, S., A study on the quadratic multiple container packing problem, Journal of the Korean Operations Research and Management Science Society, 2009, Vol. 34, No. 3, pp. 125-136.
  18. Yudhistyra, W. I., Risal Evri Marta, Raungratanaamporn I-soon, and Ratanavaraha Vatanavongs, Exploring big data research: A review of published articles from 2010 to 2018 related to logistics and supply chains, Operations and Supply Chain Management: An International Journal, 2020, Vol. 13, No. 2, pp. 134-149.