Model-Based Search for Combinatorial Optimization: A Critical Survey

@article{Zlochin2004ModelBasedSF,
  title={Model-Based Search for Combinatorial Optimization: A Critical Survey},
  author={Mark Zlochin and M. Birattari and Nicolas Meuleau and Marco Dorigo},
  journal={Annals of Operations Research},
  year={2004},
  volume={131},
  pages={373-395}
}
In this paper we introduce model-based search as a unifying framework accommodating some recently proposed metaheuristics for combinatorial optimization such as ant colony optimization, stochastic gradient ascent, cross-entropy and estimation of distribution methods. We discuss similarities as well as distinctive features of each method and we propose some extensions. 
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Stochastic Search in Metaheuristics
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In this paper we introduce model-based search as a unifying framework accommodating some recently proposed heuristics for combinatorial optimization such as ant colony optimization, stochastic
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In this paper we introduce model-based search as a unifying framework accommodating some recently proposed heuristics for combinatorial optimization such as ant colony optimization, stochastic
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