Genetic Programming over Context-Free Languages with Linear Constraints for the Knapsack Problem: First Results

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@Article{bruhn:2002:ECJ,
  author =       "Peter Bruhn and Andreas Geyer-Schulz",
  title =        "Genetic Programming over Context-Free Languages with
                 Linear Constraints for the Knapsack Problem: First
                 Results",
  journal =      "Evolutionary Computation",
  year =         "2002",
  volume =       "10",
  number =       "1",
  pages =        "51--74",
  month =        "Spring",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, grammar-based genetic, programming,
                 combinatorial, optimization, context-free grammars,
                 with linear constraints, knapsack problems",
  broken =       "http://www.ingentaconnect.com/content/mitpress/evco/2002/00000010/00000001/art00004",
  DOI =          "doi:10.1162/106365602317301772",
  abstract =     "we introduce genetic programming over context-free
                 languages with linear constraints for combinatorial
                 optimization, apply this method to several variants of
                 the multidimensional knapsack problem, and discuss its
                 performance relative to Michalewicz's genetic algorithm
                 with penalty functions. With respect to Michalewicz's
                 approach, we demonstrate that genetic programming over
                 context-free languages with linear constraints improves
                 convergence. A final result is that genetic programming
                 over context-free languages with linear constraints is
                 ideally suited to modeling complementarities between
                 items in a knapsack problem: The more complementarities
                 in the problem, the stronger the performance in
                 comparison to its competitors.",
}

Genetic Programming entries for Peter Bruhn Andreas Geyer-Schulz

Citations