Title: Solving the 3D container ship loading planning problem by representation by rules and meta-heuristics

Authors: Anibal Tavares De Azevedo; Cassilda Maria Ribeiro; Galeno José De Sena; Antônio Augusto Chaves; Luis Leduíno Salles Neto; Antônio Carlos Moretti

Addresses: Applied Science Faculty, State University of Campinas, Rua Pedro Zaccaria, 1300, Limeira, Brazil ' Mathematics Department, State of São Paulo University, Av. Dr. Ariberto Pereira da Cunha, 333, Guaratinguetá, Brazil ' Mathematics Department, State of São Paulo University, Av. Dr. Ariberto Pereira da Cunha, 333, Guaratinguetá, Brazil ' Department of Science and Technology, Federal University of São Paulo, Rua Talim, 330, São José dos Campos, São Paulo, Brazil ' Department of Science and Technology, Federal University of São Paulo, Rua Talim, 330, São José dos Campos, São Paulo, Brazil ' Applied Science Faculty, State University of Campinas, Rua Pedro Zaccaria, 1300, Limeira, Brazil

Abstract: This paper formulates the 3D containership loading planning problem (3D CLPP) and also proposes a new and compact representation to efficiently solve it. The key objective of stowage planning is to minimise the number of container movements and also the ship's instability. The binary formulation of this problem is properly described and an alternative formulation called Representation by Rules is proposed. This new representation is combined with three metaheuristics - genetic algorithm, simulated annealing, and beam search - to solve the 3D CLPP in a manner that ensures that every solution analysed in the optimisation process is compact and feasible.

Keywords: 3D container ship stowage; combinatorial optimisation; metaheuristics; container shipping; ship loading; loading planning; stowage planning; genetic algorithms; simulated annealing; beam search.

DOI: 10.1504/IJDATS.2014.063060

International Journal of Data Analysis Techniques and Strategies, 2014 Vol.6 No.3, pp.228 - 260

Available online: 25 Jun 2014

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