In-Vehicle Loading Optimization System for the Cargo Industry

Yağmur Özen

MNG Cargo R&D Center

https://orcid.org/0000-0002-7624-156X

Mehmet Aktaş

Yıldız Technical University

https://orcid.org/0000-0001-7908-5067

Yusuf Memiş

MNG Cargo R&D Center

https://orcid.org/0000-0001-9876-3089

Didem Zülfikaroğlu

MNG Cargo R&D Center

https://orcid.org/0000-0001-9720-9668

DOI: https://doi.org/10.56038/oprd.v1i1.138

Keywords: Cargo Industry, Optimization, In-Vehicle Loading, Logistics Sector, In-Vehicle Loading Optimization


Abstract

In the intense operation in the cargo sector, by using the vehicles carrying cargo between transits more optimally, it is essential to minimize the unused idle areas inside the vehicles, to set off the vehicles in the cargo transfer centers with a correct and efficient arrangement, faster, and to increase the service quality by carrying more cargo.

For this purpose, the problem of in-vehicle loading optimization is studied within the scope of this research. Again, within the scope of this research, in-vehicle loading optimization for the cargo sector is carried out; by calculating the dimensions of the packages to be placed in the vehicle, An optimization methodology is proposed, which can ensure that the cargo packages reach the maximum number and the interior volume is minimal.

A prototype implementation of the proposed methodology has been developed. The developed prototype application will enable cargo loading planning and in-vehicle optimization of vehicles operated for companies in the cargo sector. The prototype application's success was tested on a sample vehicle loading dataset, and successful results were obtained.


References

Albayrak, E., 2013. İki Boyutlu Dikdörtgen Şekilli Stok Kesme Problemleri için Sezgisel Metasezgisel Algoritma ve Yazılım Geliştirme. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, 95s, Balıkesir

Araújo, E.J., Chaves, A.A., Salles Neto, L.L., Azevedo A.T., 2016. Pareto clustering search applied for 3D container ship loading plan problem. Expert Systems with Applications, 44, 50-57 DOI: https://doi.org/10.1016/j.eswa.2015.09.005

Daş, G.S., 2010. Solving the 3D Container Loading Problem with Metaheuristics. Gaziantep Üniversitesi Fen Bilimleri Enstitüsü, Doktora Tezi, 121s, Gazientep.

Dereli, T., Daş, G.S., 2010. Konteyner Yükleme Problemleri için Karınca Koloni Optimizasyonu Yaklaşımı. Gazi Üniversitesi Mühendislik – Mimarlık Fakültesi Dergisi, 25(4), 881-894.

Erdem, H.A., 2014. Solving Container Loading Problem with Genetic Algorithm. 15th IEEE International Symposium on Computational Intelligence and Informatics, 19-21 Kasım, Budapest, 391-396. DOI: https://doi.org/10.1109/CINTI.2014.7028707

Gehring, H., Bortfeldt, A., 1997. A Genetic Algorithm for Solving the Container Loading Problem. International Transactions in Operational Research 4, 401-418. DOI: https://doi.org/10.1111/j.1475-3995.1997.tb00095.x

Gehring, H., Bortfeldt, A., 2001. A Hybrid Genetic Algorithm for the Container Loading Problem. DOI: https://doi.org/10.1016/S0377-2217(00)00055-2

Gehring, H., Bortfeldt, A., 2002. A Parallel Genetic Algorithm for Solving the Container Loading Problem. International Transactions in Operational Research 9, 497-511. DOI: https://doi.org/10.1111/1475-3995.00369

George, J.A., Robinson, D.F., 1980. A Heuristic for Packing Boxes Into a Container. Computers & Operational Research 7, 147-156. DOI: https://doi.org/10.1016/0305-0548(80)90001-5

Kang, K., Moon, I., ve Wang, H., A hybrid genetic algorithm with a new packing strategy for the three-dimensional bin packing problem. Applied Mathematics and Computation, 2012 (1287–1299) DOI: https://doi.org/10.1016/j.amc.2012.07.036

Lim, A., Rodriguesb, B, Wang, Y. A multi-faced buildup algorithm for three-dimensional packing problems. Omega ,2003, 31,471–481 DOI: https://doi.org/10.1016/j.omega.2003.08.004

Li, X., Zhang, K. A hybrid differential evolution algorithm for multiple container loading problem with heterogeneous containers. Computers & Industrial Engineering, 2015, 90, 305–313 DOI: https://doi.org/10.1016/j.cie.2015.10.007

North Carolina History Project, (2022), Malcom P. McLean (1913 – 2001), North Carolina History, https://northcarolinahistory.org/encyclopedia/malcom-p-mclean-1913-2001 adresinden alındı

OSQP (2022) – OSQP Document, University Of Oxford, https://osqp.org/docs, adresinden alındı

Özsüt, Z., 2015. Konteyner Yükleme Problemleri için Matematiksel Modeller ve Çözüm Yöntemleri. Anadolu Üniversitesi Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, 78s, Eskişehir

Peng, Y., Zhang, D., Chin, F.Y.L., 2009. A Hybrid Simulated Annealing Algorithm for Container Loading Problem. GEC’09, June 12-14, Shanghai, China, 919-928. DOI: https://doi.org/10.1145/1543834.1543975

Sheng, L., Xiuqin, S., Changjian, C., Hongxia, Z., Dayong, S., Feiyue, W., 2017. Heuristic Algorithm for the Container Loading Problem with Multiple Constraints. Computers & Industrial Engineering 108, 149-164 DOI: https://doi.org/10.1016/j.cie.2017.04.021

Most read articles by the same author(s)