Minimizing the total waste in the one-dimensional cutting stock problem with the African buffalo optimization algorithm.

Journal: PeerJ. Computer science
Published Date:

Abstract

The one-dimensional cutting-stock problem (1D-CSP) consists of obtaining a set of items of different lengths from stocks of one or different lengths, where the minimization of waste is one of the main objectives to be achieved. This problem arises in several industries like wood, glass, and paper, among others similar. Different approaches have been designed to deal with this problem ranging from exact algorithms to hybrid methods of heuristics or metaheuristics. The African Buffalo Optimization (ABO) algorithm is used in this work to address the 1D-CSP. This algorithm has been recently introduced to solve combinatorial problems such as travel salesman and bin packing problems. A procedure was designed to improve the search by taking advantage of the location of the buffaloes just before it is needed to restart the herd, with the aim of not to losing the advance reached in the search. Different instances from the literature were used to test the algorithm. The results show that the developed method is competitive in waste minimization against other heuristics, metaheuristics, and hybrid approaches.

Authors

  • Leonardo Javier Montiel-Arrieta
    AAIyA-ICBI-UAEH, Mineral de la Reforma, Hidalgo, Mexico.
  • Irving Barragan-Vite
    AAIyA-ICBI-UAEH, Mineral de la Reforma, Hidalgo, Mexico.
  • Juan Carlos Seck-Tuoh-Mora
    AAIyA-ICBI-UAEH, Mineral de la Reforma, Hidalgo, Mexico.
  • Norberto Hernandez-Romero
    AAIyA-ICBI-UAEH, Mineral de la Reforma, Hidalgo, Mexico.
  • Manuel González-Hernández
    AAIyA-ICBI-UAEH, Mineral de la Reforma, Hidalgo, Mexico.
  • Joselito Medina-Marin
    AAIyA-ICBI-UAEH, Mineral de la Reforma, Hidalgo, Mexico.

Keywords

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