• DocumentCode
    1841053
  • Title

    A Hybrid Algorithm for Solving the Optimal Layout Problem of Rectangular Pieces

  • Author

    Jiang, Xingbo ; Lu, Xiaoqing ; Liu, Chengcheng ; Li, Monan

  • Author_Institution
    Inst. of Comput. Sci. & Technol., Peking Univ., Beijing
  • fYear
    2008
  • fDate
    18-21 Nov. 2008
  • Firstpage
    936
  • Lastpage
    941
  • Abstract
    In this paper, a hybrid algorithm, combined the adaptive simulated annealing genetic algorithm with the improved bottom-left algorithm, is presented for the optimal layout problem of rectangle pieces which is a NP-complete problem and possesses widespread applications in the industry. Adaptive genetic algorithm is adopted to change the probabilities of crossover and mutation automatically. Simulated annealing algorithm is used to modify the individuals whose fitness value is higher than the average fitness value of the population. The presented algorithm provides with global search capability of adaptive genetic algorithm and local search capability of simulated annealing algorithm. The computation results show that the optimal layout problem of rectangular pieces can be effectively solved by the hybrid algorithm.
  • Keywords
    computational complexity; computational geometry; genetic algorithms; industrial engineering; probability; search problems; simulated annealing; NP-complete problem; adaptive simulated annealing genetic algorithm; bottom-left algorithm; crossover probability; fitness value; global search capability; hybrid algorithm; local search capability; mutation probability; optimal rectangular piece layout problem; Biomedical engineering; Computational modeling; Computer science; Containers; Genetic algorithms; Heuristic algorithms; Military computing; NP-complete problem; Robustness; Simulated annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3398-8
  • Electronic_ISBN
    978-0-7695-3398-8
  • Type

    conf

  • DOI
    10.1109/ICYCS.2008.425
  • Filename
    4709100