New Insights Into Diversification of Hyper-Heuristics

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@Article{Ren:2014:ieeeCybernetics,
  author =       "Zhilei Ren and He Jiang and Jifeng Xuan and Yan Hu and 
                 Zhongxuan Luo",
  title =        "New Insights Into Diversification of
                 Hyper-Heuristics",
  journal =      "IEEE Transactions on Cybernetics",
  year =         "2014",
  volume =       "44",
  number =       "10",
  month =        oct,
  pages =        "1747--1761",
  keywords =     "genetic algorithms, genetic programming,
                 Hyper-heuristics, Ising spin glass, instance
                 perturbation, linear genetic programming, p-median",
  DOI =          "doi:10.1109/TCYB.2013.2294185",
  ISSN =         "2168-2267",
  abstract =     "There has been a growing research trend of applying
                 hyper-heuristics for problem solving, due to their
                 ability of balancing the intensification and the
                 diversification with low level heuristics.
                 Traditionally, the diversification mechanism is mostly
                 realised by perturbing the incumbent solutions to
                 escape from local optima. In this paper, we report our
                 attempt toward providing a new diversification
                 mechanism, which is based on the concept of instance
                 perturbation. In contrast to existing approaches, the
                 proposed mechanism achieves the diversification by
                 perturbing the instance under solving, rather than the
                 solutions. To tackle the challenge of incorporating
                 instance perturbation into hyper-heuristics, we also
                 design a new hyper-heuristic framework HIP-HOP
                 (recursive acronym of HIP-HOP is an instance
                 perturbation-based hyper-heuristic optimisation
                 procedure), which employs a grammar guided high level
                 strategy to manipulate the low level heuristics. With
                 the expressive power of the grammar, the constraints,
                 such as the feasibility of the output solution could be
                 easily satisfied. Numerical results and statistical
                 tests over both the Ising spin glass problem and the
                 p-median problem instances show that HIP-HOP is able to
                 achieve promising performances. Furthermore, run time
                 distribution analysis reveals that, although being
                 relatively slow at the beginning, HIP-HOP is able to
                 achieve competitive solutions once given sufficient
                 time.",
  notes =        "Also known as \cite{6690192}",
}

Genetic Programming entries for Zhilei Ren He Jiang Jifeng Xuan Yan Hu Zhongxuan Luo

Citations