Genetic and hybrid algorithms to solve the container stacking problem at Tripoli-Lebanon seaport

Nobar Kassabian, Zakaria Hammoudan, Olivier Grunder and Lhassane Idoumghar

International Journal of Operational Research, 2025, vol. 53, issue 2, 201-227

Abstract: Several factors determined the survival of the seaport: logistics, storage and distribution. A storage strategy dependent on container stacking rules is an important factor in the competence of the container terminal. This article focuses on solving the problem of stacking incoming containers in the storage yard, taking into account several criteria regarding the port of Tripoli-Lebanon. A mathematical model with a mixed integer linear program for the container stacking problem is considered in this paper. As this problem is NP-hard, large instances cannot be solved by optimisation solvers as Gurobi. We develop four algorithms to tackle this problem: a genetic algorithm (GA), a randomised greedy algorithm (RGA), an iterated local search (ILS) and a hybridisation approach between RGA and ILS. Finally, numerical simulations prove the efficiency of the GA which produces results close to the optimal solution on real instances taken from the containers terminal for small and medium sizes.

Keywords: container stacking problem; CSP; mathematical modelling; optimisation; Gurobi optimiser; genetic algorithm; GA; randomise greedy algorithm; RGA; iterated local search; ILS; hybridisation. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=146897 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:53:y:2025:i:2:p:201-227

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().