An Attribute Grammar Decoder for the 01
MultiConstrained Knapsack Problem
R. Cleary, and M. O'Neill. Evolutionary Computation in Combinatorial Optimization
-- EvoCOP~2005, volume 3448 of LNCS, page 34--45. Lausanne, Switzerland, Springer Verlag, (30 March-1 April 2005)
Abstract
We describe how the standard genotype-phenotype
mapping process of Grammatical Evolution (GE) can be
enhanced with an attribute grammar to allow GE to
operate as a decoder-based Evolutionary Algorithm (EA).
Use of an attribute grammar allows GE to maintain
context-sensitive and semantic information pertinent to
the capacity constraints of the 01 Multi-constrained
Knapsack Problem (MKP). An attribute grammar
specification is used to perform decoding similar to a
first-fit heuristic. The results presented are
encouraging, demonstrating that GE in conjunction with
attribute grammars can provide an improvement over the
standard context-free mapping process for problems in
this domain.
%0 Conference Paper
%1 cleary:2005:AAGDFR0MKP
%A Cleary, Robert
%A O'Neill, Michael
%B Evolutionary Computation in Combinatorial Optimization
-- EvoCOP~2005
%C Lausanne, Switzerland
%D 2005
%E Raidl, Günther R.
%E Gottlieb, Jens
%I Springer Verlag
%K algorithms, attribute computation, evolution, evolutionary genetic grammar grammatical programming,
%P 34--45
%T An Attribute Grammar Decoder for the 01
MultiConstrained Knapsack Problem
%V 3448
%X We describe how the standard genotype-phenotype
mapping process of Grammatical Evolution (GE) can be
enhanced with an attribute grammar to allow GE to
operate as a decoder-based Evolutionary Algorithm (EA).
Use of an attribute grammar allows GE to maintain
context-sensitive and semantic information pertinent to
the capacity constraints of the 01 Multi-constrained
Knapsack Problem (MKP). An attribute grammar
specification is used to perform decoding similar to a
first-fit heuristic. The results presented are
encouraging, demonstrating that GE in conjunction with
attribute grammars can provide an improvement over the
standard context-free mapping process for problems in
this domain.
@inproceedings{cleary:2005:AAGDFR0MKP,
abstract = {We describe how the standard genotype-phenotype
mapping process of Grammatical Evolution (GE) can be
enhanced with an attribute grammar to allow GE to
operate as a decoder-based Evolutionary Algorithm (EA).
Use of an attribute grammar allows GE to maintain
context-sensitive and semantic information pertinent to
the capacity constraints of the 01 Multi-constrained
Knapsack Problem (MKP). An attribute grammar
specification is used to perform decoding similar to a
first-fit heuristic. The results presented are
encouraging, demonstrating that GE in conjunction with
attribute grammars can provide an improvement over the
standard context-free mapping process for problems in
this domain.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {Lausanne, Switzerland},
author = {Cleary, Robert and O'Neill, Michael},
biburl = {https://www.bibsonomy.org/bibtex/23bf90b68241d0e5ad1f0bcbc34e60064/brazovayeye},
booktitle = {Evolutionary Computation in Combinatorial Optimization
-- {EvoCOP}~2005},
editor = {Raidl, G{\"{u}}nther R. and Gottlieb, Jens},
interhash = {2020bb7aa314fbc9142fbc3b95f246e1},
intrahash = {3bf90b68241d0e5ad1f0bcbc34e60064},
issn = {0302-9743},
keywords = {algorithms, attribute computation, evolution, evolutionary genetic grammar grammatical programming,},
month = {30 March-1 April},
notes = {EvoCOP2005 Also known as \cite{cleary:evocop05}},
pages = {34--45},
publisher = {Springer Verlag},
publisher_address = {Berlin},
series = {LNCS},
timestamp = {2008-06-19T17:37:59.000+0200},
title = {An Attribute Grammar Decoder for the 01
MultiConstrained Knapsack Problem},
volume = 3448,
year = 2005
}