Evolutionary Computation and Convergence to a Pareto Front

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{VanVeldhuizen:1998:eccpf,

• author = "David A. {Van Veldhuizen} and Gary B. Lamont",
• title = "Evolutionary Computation and Convergence to a {Pareto} Front",
• booktitle = "Late Breaking Papers at the Genetic Programming 1998 Conference",
• year = "1998",
• editor = "John R. Koza",
• pages = "221--228",
• address = "University of Wisconsin, Madison, Wisconsin, USA",
• publisher_address = "Stanford, CA, USA",
• month = "22-25 " # jul,
• publisher = "Stanford University Bookstore",
• keywords = "genetic algorithms, genetic programming, MOP, GA, ES, GP, EP",
• URL = "http://www.lania.mx/~ccoello/EMOO/vanvel2.ps.gz",
• size = "7.1 pages",
• 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.",
• notes = "Matlab, GEATbx GP-98LB",

}

Genetic Programming entries for David A Van Veldhuizen Gary B Lamont

Citations