Genetic Programming over Context-Free Languages with Linear Constraints for the Knapsack Problem: First Results
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @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