Moussi, Riadh; Ndiaye, Ndèye Fatma; Yassine, Adnan Hybrid genetic simulated annealing algorithm (HGSAA) to solve storage container problem in port. (English) Zbl 1336.90109 Pan, Jeng-Shyang (ed.) et al., Intelligent information and database systems. 4th Asian conference, ACIIDS 2012, Kaohsiung, Taiwan, March 19–21, 2012. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-28489-2/pbk). Lecture Notes in Computer Science 7197. Lecture Notes in Artificial Intelligence, 301-310 (2012). Summary: Container terminals play an important role in marine transportation; they constitute transfer stations to multimodal transport. In this paper, we study the storage of containers. We model the seaport system as a container location model, with an objective function designed to minimize the distance between the vessel berthing locations and the storage zone. Due to the inherent complexity of the problem, we propose a hybrid algorithm based on genetic (GA) and simulated annealing (SA) algorithm. In this paper, three different forms of integration between GA and SA are developed. In order to prove the efficiency of the HGSAAs proposed are compared to the optimal solutions for small-scale problems of an exact method which is Branch and Bound using the commercial software ILOG CPLEX. Computational results on real dimensions taken from the terminal of Normandy, Le Havre port, France, show the good quality of the solutions obtained by the HGSAAs.For the entire collection see [Zbl 06018408]. Cited in 1 ReviewCited in 1 Document MSC: 90C59 Approximation methods and heuristics in mathematical programming 90B90 Case-oriented studies in operations research 90B05 Inventory, storage, reservoirs Keywords:container terminal; storage container; hybrid genetic simulated annealing algorithm (HGSAA) Software:CPLEX PDF BibTeX XML Full Text: DOI References:  Bourazza, S.: Variants of genetic algorithms applied to scheduling problems. 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