Theory of Evolutionary Algorithms and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@InCollection{droste:2003:ACI,

• author = "Stefan Droste and Thomas Jansen and G{\"u}nter Rudolph and Hans-Paul Schwefel and Karsten Tinnefeld and Ingo Wegener",
• title = "Theory of Evolutionary Algorithms and Genetic Programming",
• booktitle = "Advances in Computational Intelligence: Theory and Practice",
• publisher = "Springer",
• year = "2003",
• editor = "Hans-Paul Schwefel and Ingo Wegener and Klaus Weinert",
• series = "Natural Computing Series",
• chapter = "5",
• pages = "107--144",
• keywords = "genetic algorithms, genetic programming, NFL, Evolutionary Algorithms, Multiobjective Evolutionary Algorithms, Crossover, Takeover Times",
• ISBN = "3-540-43269-8",
• URL = "http://www.springer.com/computer/ai/book/978-3-540-43269-2",
• DOI = "doi:10.1007/978-3-662-05609-7_5",
• abstract = "Randomised search heuristics are an alternative to specialised and problem-specific algorithms. They are applied to NP-hard problems with the hope of being efficient in typical cases. They are an alternative if no problem-specific algorithm is available. And they are the only choice in black-box optimisation where the function to be optimised is not known. Evolutionary algorithms (EA) are a special class of randomised algorithms with many successful applications. However, the theory of evolutionary algorithms is in its infancy. Here many new contributions to constructing such a theory are presented and discussed.",
• notes = "Dynamization and Adaptation. Black-box Optimisation. Metric-Based EA (MBEA) and an Application in GP",

}

Genetic Programming entries for Stefan Droste Thomas Jansen Guenter Rudolph Hans-Paul Schwefel Karsten Tinnefeld Ingo Wegener

Citations