• DocumentCode
    2852706
  • Title

    EPSO for solving non-oriented two-dimensional bin packing problem

  • Author

    Omar, Mohamed K. ; Ramakrishnan, Kumaran

  • Author_Institution
    Bus. Sch. - Malaysia, Nottingham Univ., Semenyih, Malaysia
  • fYear
    2011
  • fDate
    6-9 Dec. 2011
  • Firstpage
    106
  • Lastpage
    110
  • Abstract
    The non-oriented two-dimensional bin packing problem is dealing with a set of rectangular pieces that need to be packed into identical rectangular bins. Moreover and in order to minimize the number of bins, the pieces are allowed to rotate by 90° without overlapping. There are many real life applications for this operations research problem. Among these applications: loading of boxes to pallets, trucks and containers, packing of box bases on shelves and other applications in the wood and metal industry. In this paper, we propose evolutionary particle swarm optimization algorithm (EPSO) for solving the non-oriented two-dimensional bin packing problem. Extensive numerical investigations are performed to determine the solution quality of the proposed algorithm. Moreover, the performance of our proposed algorithm is compared with a best known greedy algorithm published in the literature.
  • Keywords
    bin packing; evolutionary computation; greedy algorithms; palletising; particle swarm optimisation; EPSO; evolutionary particle swarm optimization algorithm; greedy algorithm; identical rectangular bins; metal industry; nonoriented two-dimensional bin packing problem; numerical investigations; operations research problem; wood industry; Algorithm design and analysis; Approximation algorithms; Birds; Europe; Genetic algorithms; Particle swarm optimization; Strips; Bin packing; evolutionary particle swarm optimization algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on
  • Conference_Location
    Singapore
  • ISSN
    2157-3611
  • Print_ISBN
    978-1-4577-0740-7
  • Electronic_ISBN
    2157-3611
  • Type

    conf

  • DOI
    10.1109/IEEM.2011.6117888
  • Filename
    6117888