Multiobjective genetic programming approach to evolving heuristics for the bounded diameter minimum spanning tree problem: MOGP for BDMST

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@InProceedings{DBLP:conf/gecco/KumarBR09,
  author =       "Rajeev Kumar and Bipul Kumar Bal and Peter Rockett",
  title =        "Multiobjective genetic programming approach to
                 evolving heuristics for the bounded diameter minimum
                 spanning tree problem: MOGP for BDMST",
  booktitle =    "GECCO '09: Proceedings of the 11th Annual conference
                 on Genetic and evolutionary computation",
  year =         "2009",
  editor =       "Guenther Raidl and Franz Rothlauf and 
                 Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and 
                 Mauro Birattari and Clare Bates Congdon and 
                 Martin Middendorf and Christian Blum and Carlos Cotta and 
                 Peter Bosman and Joern Grahl and Joshua Knowles and 
                 David Corne and Hans-Georg Beyer and Ken Stanley and 
                 Julian F. Miller and Jano {van Hemert} and 
                 Tom Lenaerts and Marc Ebner and Jaume Bacardit and 
                 Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and 
                 Thomas Jansen and Riccardo Poli and Enrique Alba",
  pages =        "309--316",
  address =      "Montreal",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "8-12 " # jul,
  organisation = "SigEvo",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-60558-325-9",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  DOI =          "doi:10.1145/1569901.1569945",
  abstract =     "The bounded-diameter (or diameter-constrained) minimum
                 spanning tree (BDMST) problem is a well-studied
                 combinatorial optimization problem for which several
                 heuristics such as: one-time tree construction (OTTC),
                 center based tree construction(CBTC), iterative
                 refinement (IR) and randomized greedy heuristics (RGH)
                 have been developed. Very little work, however, has
                 been done on producing heuristics for BDMSTs using
                 evolutionary algorithms. In this paper we have used
                 multiobjective genetic programming (MOGP) to explore
                 the evolution of a set of heuristics for the BDMST
                 problem. The quality of the Pareto fronts obtained from
                 the MOGP-evolved heuristics is comparable to, or in
                 some cases better than, the Pareto fronts generated by
                 established, hand-crafted heuristics. MOGP is thus a
                 very promising technique for finding heuristics for
                 BDMSTs and more general multiobjective combinatorial
                 optimizations.",
  notes =        "GECCO-2009 A joint meeting of the eighteenth
                 international conference on genetic algorithms
                 (ICGA-2009) and the fourteenth annual genetic
                 programming conference (GP-2009).

                 ACM Order Number 910092.",
}

Genetic Programming entries for Rajeev Kumar Bipul Kumar Bal Peter I Rockett

Citations