Fitness Landscape based Parameter Estimation for Robust Taboo Search
Created by W.Langdon from
gp-bibliography.bib Revision:1.7975
- @InProceedings{3360,
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author = "Andreas Beham and Erik Pitzer and
Michael Affenzeller",
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title = "Fitness Landscape based Parameter Estimation for
Robust Taboo Search",
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booktitle = "Computer Aided Systems Theory, Eurocast 2013",
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year = "2013",
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editor = "Roberto Moreno-Diaz and Franz Pichler and
Alexis Quesada-Arencibia",
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volume = "8111",
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series = "LNCS",
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pages = "292--299",
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address = "Las Palmas, Spain",
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month = "10-15 " # feb,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Problem
Instance, Problem Size, Fitness Landscape, Quadratic
Assignment Problem, Large Problem Size",
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isbn13 = "978-3-642-53856-8",
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URL = "https://link.springer.com/chapter/10.1007/978-3-642-53856-8_37",
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DOI = "doi:10.1007/978-3-642-53856-8_37",
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abstract = "Metaheuristic optimization algorithms are general
optimization strategies suited to solve a range of
real-world relevant optimization problems. Many
metaheuristics expose parameters that allow to tune the
effort that these algorithms are allowed to make and
also the strategy and search behaviour [1]. Adjusting
these parameters allows to increase the algorithms
performances with respect to different problem- and
problem instance characteristics.",
- }
Genetic Programming entries for
Andreas Beham
Erik Pitzer
Michael Affenzeller
Citations