The dynamic programming model for optimal allocation of laden shipping containers to Nigerian seaports

• Autorzy: Amuji Harrison O. , Onwuegbuchunam Donatus E. , Aponjolosun Moses O. , Okeke Kenneth O. , Mbachu Justice C. , Ojutalayo John F.

Identyfikatory

DOI

10.14254/jsdtl.2022.7-2.5

• Języki publikacji: EN

Abstrakty

EN

In highly competitive shipping market environment, container network operators-Freight forwarders, shipping companies etc. are concerned about design, development and deployment of optimized allocation model to achieve cost savings through improved container storage yard operations, crane productivity, outbound container allocation/distribution to seaport terminals and hence reduction in ships’ waiting times. In this paper, we developed two models, the Dynamic programming model and optimal allocation policy (model), for the optimal allocation of units of outbound laden cargo containers of sizes: 20ft and 40ft to six (6) major seaports in Nigeria. The distributions of the laden containers were allocated as follows: Port-Harcourt, Tincan Island, Onne, and Calabar seaports were allocated with 1,064 units of stuffed containers each. Apapa seaport was allocated with 2,128 units of laden containers, and zero allocation was made to Warri seaport. These results were arrived at through the implementation of the optimal allocation policy. The zero units allocation made to Warri seaport could be attributed to poor shipper patronage and hence the low frequency of ship visits. Apapa seaport was allocated double the number of containers moved to the remaining ports because it attracted more shipper patronage and hence more ship visits. Hence, freight forwarding companies will be assured of cargo spaces and make more profit by allocating more containers. Policy implications of the developed models were discussed.

Słowa kluczowe

EN

dynamic programming; ships’ waiting times; optimal allocation policy; Nigerian seaports; loaded shipping containers

• Wydawca: Fundacja Centrum Badań Socjologicznych ; Scientific Publishing House "SciView"
• Czasopismo: Journal of Sustainable Development of Transport and Logistics
• Rocznik: 2022
• Tom: Vol. 7, No. 2
• Strony: 69--79
• Opis fizyczny: Bibliogr. 16 poz., tab., wzory

Twórcy

autor

Amuji Harrison O.

• Department of Statistics, Department of Maritime Management Technology, Federal University of Technology Owerri, Nigeria

• https://orcid.org/0000-0003-2992-2431

autor

Onwuegbuchunam Donatus E.

• Department of Maritime Management Technology, Federal University of Technology, Owerri, Nigeria

• https://orcid.org/0000-0003-2120-9922

autor

Aponjolosun Moses O.

• Department of Maritime Management Technology, Federal University of Technology, Owerri, Nigeria

• https://orcid.org//0000-0002-3656-7370

autor

Okeke Kenneth O.

• Department of Maritime Management Technology, Federal University of Technology, Owerri, Nigeria

autor

Mbachu Justice C.

• Department of Maritime Management Technology, Federal University of Technology, Owerri, Nigeria

autor

Ojutalayo John F.

• Department of Nautical Science, Federal College of Fisheries and Marine Technology, Victoria Island, Lagos, Nigeria

Bibliografia

• Adelson, R. M., Norman, J. M., & Laporte, G. (1976). A dynamic programming formulation with diverse applications. Operational Research Quarterly, 119-121.
• Amuji, H. O., Ugwuanyim, G. U., Ogbonna, C. J., Iwu, H. C., & Okechukwu, B. N. (2017). The usefulness of dynamic programming in course allocation in the Nigerian Universities. Open Journal of Optimization, 6(4), 176-186. https://doi.org/10.4236/ ojop.2017.64012
• Augustine, O. E., & Barry, R.M. (1974). Non-Serial Dynamic Programming: A Survey. Palgrave Macmillan Journals, 25, 253-265.
• Chen, K., Lu, Q., Xin, X., Yang, Z., Zhu, L., & Xu, Q. (2022). Optimization of empty container allocation for inland freight stations considering stochastic demand. Ocean & Coastal Management, 230(1), 1-10. https://doi.org/10.1016/j.ocecoaman.2022.106366
• Cobo, P.T. (2016) Optimization of yard operations in container terminals from an energy efficiency approach. Unpublished PhD Thesis. Industrial PhD Pilot program in Civil Engineering, Universidad Politécnica de Cataluña - Barcelona Tech.
• Armas, L. D., Valdes, D., Morell, C., & Bello, R. (2019). Solutions to storage spaces allocation problem for import containers by exact and heuristic methods. Computación y Sistemas, 23(1), 197-211. https://doi.org/10.13053/CyS-23-1-2916
• Dhahri, M., Mezghani, M., & Rekik, I. (2020). A Weighted Goal Programming model for Storage Space Allocation problem in a container terminal. Journal of Sustainable Development of Transport and Logistics, 5(2), 6-21. https://doi.org/10.14254/jsdtl.2020.5-2.1
• Facchini, F., Boenzi, F., Digiesi, S., & Mummolo, G. (2018). A model-based Decision Support System for multiple container terminals hub management. Production, 28, e20170074. https://doi.org/10.1590/0103-6513.20170074.
• Guo, W., Atasoy, B., Beelaerts van Blokland, W., & Negenborn, R. R. (2020). Dynamic and stochastic shipment matching problem in multimodal transportation. Transportation Research Record, 2674(2), 262-273.
• Howard, R. A. (1966). Dynamic programming. Management Science, 12(5), 317-348.
• Jacquin, S., Jourdan, L., & Talbi, E. G. (2016). A multi-objective dynamic programming-based metaheuristic to solve a bi-objective unit commitment problem using a multi-objective decoder. International Journal of Metaheuristics, 5(1), 3-30.
• Moores, B. (1986). Dynamic programming in transformer design. Journal of the Operational Research Society, 37, 967-969.
• Onwuegbuchunam, D. E. (2018). Assessing port governance, devolution and terminal performance in Nigeria. Logistics, 2(1), 6. https://doi.org/10.3390/logistics2010006
• Peter, S. (1989). Dynamic Programming in Action. Palgrave Macmillan Journals, 40, 779-787.
• Wong, P. J. (1970). A new decomposition procedure for dynamic programming. Operations Research, 18(1), 119-131.
• Xu, Y., Wang, M., Lai, K. K., & Ram, B. (2022). A stochastic model for shipping container terminal storage management. Journal of Marine Science and Engineering, 10(10), 1429. https://doi.org/10.3390/jmse10101429

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).