Restricted Evaluation Genetic Algorithms with Tabu Search for Optimising Boolean Functions as Multi-Level AND-EXOR Networks
Created by W.Langdon from
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- @InProceedings{750023,
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author = "Julian F. Miller and Peter Thomson",
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title = "Restricted Evaluation Genetic Algorithms with Tabu
Search for Optimising {Boolean} Functions as
Multi-Level {AND-EXOR} Networks",
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booktitle = "Selected Papers from AISB Workshop on Evolutionary
Computing",
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year = "1996",
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ISBN = "3-540-61749-3",
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pages = "85--101",
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publisher = "Springer-Verlag",
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address = "Brighton, U.K.",
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month = "1-2 " # apr,
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series = "LNCS",
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volume = "1143",
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editor = "Terence C. Fogarty",
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keywords = "genetic algorithms, genetic programming",
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URL = "https://rdcu.be/dgo0t",
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DOI = "doi:10.1007/BFb0032775",
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abstract = "In GAs applied to engineering problems (in our case,
the optimisation of logic circuits) the fitness
function is usually complex and the fitness evaluation
is time consuming. The run time is therefore a major
consideration when designing a GA for optimisation,
thus a look-up table for fitness evaluation is
desirable. As a consequence, it is appropriate to limit
the number of different chromosome fitness evaluations
that any particular run of the GA will be allowed to
examine. In this situation the user is uninterested in
the number of generations required. It is necessary in
this approach to guarantee the users that they will be
able to find a good and reliable problem solution
within the limited number of evaluations, and hence
time available. We refer to this type of GA as a
restricted evaluation GA. In this paper we suggest a
number of hybrid algorithms which combine a GA with a
neighbourhood search (TABU) technique to provide this
performance and reliability. The effectiveness of each
of these methods is compared and contrasted, and
underlying principles are suggested as to why these
techniques might prove to be useful in these types of
problem.",
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notes = "305 pp., Softcover",
- }
Genetic Programming entries for
Julian F Miller
Peter Thomson
Citations