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

Author

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

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.

Suggested Citation

  • Anibal Tavares De Azevedo & Cassilda Maria Ribeiro & Galeno José De Sena & Antônio Augusto Chaves & Luis Leduíno Salles Neto & Antônio Carlos Moretti, 2014. "Solving the 3D container ship loading planning problem by representation by rules and meta-heuristics," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 6(3), pages 228-260.
    • Handle: RePEc:ids:injdan:v:6:y:2014:i:3:p:228-260
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