An Analysis and Evaluation of the Saving Capability and Feasibility of Backward-Chaining Evolutionary Algorithms
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- @InProceedings{DBLP:conf/acal/XieZ09,
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author = "Huayang Xie and Mengjie Zhang",
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title = "An Analysis and Evaluation of the Saving Capability
and Feasibility of Backward-Chaining Evolutionary
Algorithms",
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booktitle = "Proceedings of the 4th Australian Conference on
Artificial Life (ACAL'09)",
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series = "Lecture Notes in Computer Science",
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volume = "5865",
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year = "2009",
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editor = "Kevin B. Korb and Marcus Randall and Tim Hendtlass",
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pages = "63--72",
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address = "Melbourne, Australia",
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month = dec # " 1-4",
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publisher = "Springer",
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bibsource = "DBLP, http://dblp.uni-trier.de",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-642-10426-8",
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DOI = "doi:10.1007/978-3-642-10427-5_7",
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abstract = "Artificial Intelligence, volume 170, number 11, pages
953-983, 2006 published a paper titled
{"}Backward-chaining evolutionary algorithm{"}
\cite{poli_2006_AIJ}. It introduced two fitness
evaluation saving algorithms which are built on top of
standard tournament selection. One algorithm is named
Efficient Macro-selection Evolutionary Algorithm
(EMS-EA) and the other is named Backward-chaining EA
(BC-EA). Both algorithms were claimed to be able to
provide considerable fitness evaluation savings, and
especially BC-EA was claimed to be much efficient for
hard and complex problems which require very large
populations. This paper provides an evaluation and
analysis of the two algorithms in terms of the
feasibility and capability of reducing the fitness
evaluation cost. The evaluation and analysis results
show that BC-EA would be able to provide computational
savings in unusual situations where given problems can
be solved by an evolutionary algorithm using a very
small tournament size, or a large tournament size but a
very large population and a very small number of
generations. Other than that, the saving capability of
BC-EA is the same as EMS-EA. Furthermore, the
feasibility of BC-EA is limited because two important
assumptions making it work hardly hold.",
- }
Genetic Programming entries for
Huayang Jason Xie
Mengjie Zhang
Citations