Evolutionary Computation and Convergence to a Pareto Front
Created by W.Langdon from
gp-bibliography.bib Revision:1.8110
- @InProceedings{VanVeldhuizen:1998:eccpf,
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author = "David A. {Van Veldhuizen} and Gary B. Lamont",
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title = "Evolutionary Computation and Convergence to a {Pareto}
Front",
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booktitle = "Late Breaking Papers at the Genetic Programming 1998
Conference",
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year = "1998",
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editor = "John R. Koza",
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pages = "221--228",
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address = "University of Wisconsin, Madison, Wisconsin, USA",
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publisher_address = "Stanford, CA, USA",
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month = "22-25 " # jul,
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publisher = "Stanford University Bookstore",
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keywords = "genetic algorithms, genetic programming, MOP, GA, ES,
GP, EP",
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URL = "http://www.lania.mx/~ccoello/EMOO/vanvel2.ps.gz",
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size = "7.1 pages",
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abstract = "Research into solving multiobjective optimisation
problems (MOP) has as one of its an overall goals that
of developing and defining foundations of an
Evolutionary Computation (EC)-based MOP theory. In this
paper, we introduce relevant MOP concepts, and the
notion of Pareto optimality, in particular. Specific
notation is defined and theorems are presented ensuring
Pareto based Evolutionary Algorithm (EA)
implementations are clearly understood. Then, a
specific experiment investigating the convergence of an
arbitrary EA to a Pareto front is presented. This
experiment gives a basis for a theorem showing a
specific multiobjective EA statistically converges to
the Pareto front. We conclude by using this work to
justify further exploration into the theoretical
foundations of EC-based MOP solution methods.",
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notes = "Matlab, GEATbx GP-98LB",
- }
Genetic Programming entries for
David A Van Veldhuizen
Gary B Lamont
Citations