Frequency Distribution Based Hyper-Heuristic for the Bin-Packing Problem

  • He Jiang
  • Shuyan Zhang
  • Jifeng Xuan
  • Youxi Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6622)

Abstract

In the paper, we investigate the pair frequency of low-level heuristics for the bin packing problem and propose a Frequency Distribution based Hyper-Heuristic (FDHH). FDHH generates the heuristic sequences based on a pair of low-level heuristics rather than an individual low-level heuristic. An existing Simulated Annealing Hyper-Heuristic (SAHH) is employed to form the pair frequencies and is extended to guide the further selection of low-level heuristics. To represent the frequency distribution, a frequency matrix is built to collect the pair frequencies while a reverse-frequency matrix is generated to avoid getting trapped into the local optima. The experimental results on the bin-packing problems show that FDHH can obtain optimal solutions on more instances than the original hyper-heuristic.

Keywords

hyper-heuristic frequency distribution bin-packing pair frequency 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • He Jiang
    • 1
  • Shuyan Zhang
    • 2
  • Jifeng Xuan
    • 3
  • Youxi Wu
    • 4
  1. 1.School of SoftwareDalian University of TechnologyChina
  2. 2.School of Software TechnologyZhengzhou UniversityChina
  3. 3.School of Mathematical SciencesDalian University of TechnologyChina
  4. 4.School of Computer Science and SoftwareHebei University of TechnologyChina

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