Grammar-based Selection Hyper-heuristics for Solving Irregular Bin Packing Problems

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@InProceedings{Sosa-Ascencio:2016:GECCOcomp,
  author =       "Alejandro Sosa-Ascencio and Hugo Terashima-Marin and 
                 Jose Carlos Ortiz-Bayliss and 
                 Santiago Enrique Conant-Pablos",
  title =        "Grammar-based Selection Hyper-heuristics for Solving
                 Irregular Bin Packing Problems",
  booktitle =    "GECCO '16 Companion: Proceedings of the Companion
                 Publication of the 2016 Annual Conference on Genetic
                 and Evolutionary Computation",
  year =         "2016",
  editor =       "Tobias Friedrich and Frank Neumann and 
                 Andrew M. Sutton and Martin Middendorf and Xiaodong Li and 
                 Emma Hart and Mengjie Zhang and Youhei Akimoto and 
                 Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and 
                 Daniele Loiacono and Julian Togelius and 
                 Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and 
                 Faustino Gomez and Carlos M. Fonseca and 
                 Heike Trautmann and Alberto Moraglio and William F. Punch and 
                 Krzysztof Krawiec and Zdenek Vasicek and 
                 Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and 
                 Boris Naujoks and Enrique Alba and Gabriela Ochoa and 
                 Simon Poulding and Dirk Sudholt and Timo Koetzing",
  pages =        "111--112",
  month =        "20-24 " # jul,
  organisation = "SIGEVO",
  address =      "Denver, USA",
  publisher =    "ACM",
  keywords =     "genetic algorithms, genetic programming: Poster",
  publisher_address = "New York, NY, USA",
  isbn13 =       "978-1-4503-4323-7",
  DOI =          "doi:10.1145/2908961.2908970",
  abstract =     "a grammar-based hyper-heuristic model for selecting
                 heuristics to solve the two-dimensional bin packing
                 problem (2D-PBB) with irregular pieces and regular
                 objects. We propose to use a genetic programming
                 approach to generate rules for selecting one suitable
                 heuristic according to the features that characterize
                 the problem state. The experiments confirm the idea
                 that the results produced by the proposed approach are
                 able to rival those obtained by some heuristics
                 described in the literature.",
  notes =        "Distributed at GECCO-2016.",
}

Genetic Programming entries for Alejandro Sosa-Ascencio Hugo Terashima-Marin Jose Carlos Ortiz-Bayliss Santiago Enrique Conant-Pablos

Citations