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Approach for Optimisation Warehouse Storage Areas Based on the Container Storage Problem

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Smart Applications and Data Analysis (SADASC 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1677))

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Abstract

Warehousing, is a pillar of logistics and a link in the entire Supply Chain. Thus, warehousing’s quality is dependent on the effectiveness of its multiple missions that meets several challenges (safety, security, handling equipment, design...). Sizing warehouses & Optimization of surfaces is the research focus on this paper that mainly aims and contributes to standardize the estimation of the storage area surface to be used and optimizing it. This study arises from the fact that some companies must store different equipment (with distinct dimensions and different dates of entry and exit) on the same storage area, what makes these companies fall into the warehousing hazard trap. The proposed solution of this research results from the Benchmarking study carried out on the Container Storage Problem in port terminals. In this paper, we propose a Branch and Cut algorithm which is supported by some specific storage strategies, highlighting the Operational Research as an efficient problem-solving tool. To meet the objectives and make the work a reality, a project under construction at JESA company is taken as a reference to apply the solution and implemented it through CPLEX optimization software using the Optimization Programming Language OPL.

Supported by JESA company.

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References

  1. Bazzazi, M., Safaei, N., Javadian, N.: A genetic algorithm to solve the storage space allocation problem in a container terminal. Comput. Ind. Eng. 56, 44–52 (2009). https://doi.org/10.1016/j.cie.2008.03.012

    Article  Google Scholar 

  2. Borgman, B., Asperen, E.V., Dekker, R., Borgman, B., Dekker, R., Asperen, E.V.: Online rules for container stacking. OR Spectrum 32, 687–716 (2010). https://doi.org/10.1007/S00291-010-0205-4

    Article  MATH  Google Scholar 

  3. de Castillo, B., Daganzo, C.F.: Handling strategies for import containers at marine terminals. Transp. Res. Part B: Methodol. 27, 151–166 (1993). https://doi.org/10.1016/0191-2615(93)90005-U

    Article  Google Scholar 

  4. Chen, T.: Yard operations in the container terminal-a study in the ‘unproductive moves. Marit. Policy Manag. 26, 27–38 (1999). https://doi.org/10.1080/030888399287041

    Article  Google Scholar 

  5. Cordeau, J.F., Gaudioso, M., Laporte, G., Moccia, L.: The service allocation problem at the Gioia Tauro maritime terminal. Eur. J. Oper. Res. 176, 1167–1184 (2007). https://doi.org/10.1016/j.ejor.2005.09.004

    Article  MATH  Google Scholar 

  6. Daroudi, S., Kazemipoor, H., Najafi, E., Fallah, M.: The minimum latency in location routing fuzzy inventory problem for perishable multi-product materials. Appl. Soft Comput. 110 (2021). https://doi.org/10.1016/j.asoc.2021.107543

  7. Dekker, R., Voogd, P., Asperen, E.V.: Advanced methods for container stacking. undefined 28, October 2006. DOI:https://doi.org/10.1007/S00291-006-0038-3

  8. Dubreuil, J.: La logistique des terminaux portuaires de conteneurs (2007)

    Google Scholar 

  9. Duinkerken, M.B., Evers, J.J.M., Ottjes, J.A.: A simulation model for integrating quay transport and stacking policies on automated container terminals (2001)

    Google Scholar 

  10. Garouani, M., Ahmad, A., Bouneffa, M., Hamlich, M., Bourguin, G., Lewandowski, A.: Towards big industrial data mining through explainable automated machine learning. Int. J. Adv. Manuf. Technol. 120(1–2), 1169–1188 (2022). https://doi.org/10.1007/s00170-022-08761-9, https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124533422 &doi=10.1007%2fs00170-022-08761-9 &partnerID=40 &md5=6f8acb109c7fd98e61501acf73a737a8

  11. Hajjem, I.A.: Techniques avancées d’optimisation pour la résolution du problème de stockage de conteneurs dans un port. Ph.D. thesis, https://tel.archives-ouvertes.fr/tel-01266169

  12. Hamlich, M., Ramdani, M.: Data classification by sac “scout ants for clustering” algorithm. J. Theoret. Appl. Inf. Technol. 55(1), 66–73 (2013). https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883869002 &partnerID=40 &md5=9ed20bcce68fa42017efbb142170865a

  13. Kefi, M.: Optimisation Heuristique Distribuée du Problème de Stockage de Conteneurs dans un Port. Ph.D. thesis. https://tel.archives-ouvertes.fr/tel-00366467

  14. Kekana, P., Bakama, E.M., Mukwakungu, S.C., Sukdeo, N.: The impact of smart-warehousing on a local foodservice equipment-company’s external customers, vol. 2020-December, pp. 771–775. IEEE Computer Society, December 2020. https://doi.org/10.1109/IEEM45057.2020.9309751

  15. Khaoula, C.: Optimisation des mouvements des conteneurs dans un terminal maritime. Ph.D. thesis (12). https://publications.polymtl.ca/737/1/2011_KhaoulaChebil.pdf

  16. Luo, S., Choi, T.M.: Operational research for technology-driven supply chains in the industry 4.0 era: recent development and future studies. Asia-Pacific J. Oper. Res. (2020). https://doi.org/10.1142/S0217595920400217

  17. Ma, Y., Kim, K.H.: A comparative analysis: various storage rules in container yards and their performances. Ind. Eng. Manage. Syst. 11, 276–287 (2012). https://doi.org/10.7232/iems.2012.11.3.276

    Article  Google Scholar 

  18. Mirghaderi, S.D., Modiri, M.: Application of meta-heuristic algorithm for multi-objective optimization of sustainable supply chain uncertainty. https://doi.org/10.1007/s12046-020-01554-4S

  19. Moncef, G., Adeel, A., Mourad, B., Mohamed, H.: Amlbid: An auto-explained automated machine learning tool for big industrial data. SoftwareX 17 (2022). https://doi.org/10.1016/j.softx.2021.100919, https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121265920 &doi=10.1016%2fj.softx.2021.100919 &partnerID=40 &md5=7f168872e6185c17a3079221d35a7d14

  20. Ndiaye, N.F.: Algorithmes d’optimisation pour la résolution du problème de stockage de conteneurs dans un terminal portuaire. Ph.D. thesis. https://tel.archives-ouvertes.fr/tel-01255365/document

  21. Pandian, D.A.P.: Artificial intelligence application in smart warehousing environment for automated logistics. J. Artif. Intell. Capsule Networks 2019, 63–72 (2019). https://doi.org/10.36548/jaicn.2019.2.002

    Article  Google Scholar 

  22. Singh, S., Kumar, P., Bhandari, M., Soni, G.: Risk management for e-commerce supply chain network using robust optimization approach: a case study. In: Natarajan, S.K., Prakash, R., Sankaranarayanasamy, K. (eds.) Recent Advances in Manufacturing, Automation, Design and Energy Technologies. LNME, pp. 35–46. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-4222-7_5 https://shortest.link/1-4O

    Chapter  Google Scholar 

  23. Saanen, Y.A., Dekker, R.: Intelligent stacking as way out of congested yards ? part 1. Port Technology (2007). https://www.porttechnology.org/technical-papers/intelligent_stacking_as_way_out_of_congested_yards_part_1/

  24. Taleb-Ibrahimi, M., de Castilho, B., Daganzo, C.F.: Storage space vs handling work in container terminals. Transportation Research Part B: Methodological 27(1), 13–32 (1993). https://EconPapers.repec.org/RePEc:eee:transb:v:27:y:1993:i:1:p:13–32

    Article  Google Scholar 

  25. Zheng, M., Du, N., Zhao, H., Huang, E., Wu, K.: A study on the optimal inventory allocation for clinical trial supply chains. Appl. Math. Modelling 98, 161–184 (2021). https://doi.org/10.1016/j.apm.2021.04.029

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Manal Ayad .

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Ayad, M., Siadat, A. (2022). Approach for Optimisation Warehouse Storage Areas Based on the Container Storage Problem. In: Hamlich, M., Bellatreche, L., Siadat, A., Ventura, S. (eds) Smart Applications and Data Analysis. SADASC 2022. Communications in Computer and Information Science, vol 1677. Springer, Cham. https://doi.org/10.1007/978-3-031-20490-6_22

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  • DOI: https://doi.org/10.1007/978-3-031-20490-6_22

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