Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/4288

TitleA study of order based genetic and evolutionary algorithms in combinatorial optimization problems
Author(s)Rocha, Miguel
Vilela, Carla
Neves, José
KeywordsGenetic algorithms
Genetic diversity
The traveling salesman problem
Order-based representations
genetic and evolutionary algorithms
Issue date2000
PublisherSpringer
JournalLecture Notes in Artificial Intelligence (subseries of Lecture Notes in Computer Science)
Abstract(s)In Genetic and Evolutionary Algorithms (GEAs) one is faced with a given number of parameters, whose possible values are coded in a binary alphabet. With Order Based Representations (OBRs) the genetic information is kept by the order of the genes and not by its value. The application of OBRs to the Traveling Salesman Problem (TSP) is a well known technique to the GEA community. In this work one intends to show that this coding scheme can be used as an indirect representation, where the chromosome is the input for the decoder. The behavior of the GEA's operators is compared under benchmarks taken from the Combinatorial Optimization arena.
TypeConference paper
URIhttp://hdl.handle.net/1822/4288
ISBN3540676899
DOI10.1007/3-540-45049-1_72
ISSN0302-9743
Peer-Reviewedyes
AccessOpen access
Appears in Collections:DI/CCTC - Artigos (papers)

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