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- W2131330491 abstract "Evolutionary algorithms and other nature-inspired search heuristics like ant colony optimization have been shown to be very successful when dealing with real-world applications or problems from combinatorial optimization. In recent years, analyses has shown that these general randomized search heuristics can be analyzed like ordinary randomized algorithms and that such analyses of the expected optimization time yield deeper insights in the functioning of evolutionary algorithms in the context of approximation and optimization. This is an important research area where a lot of interesting questions are still open.The tutorial enables attendees to analyze the computational complexity of evolutionary algorithms and other search heuristics in a rigorous way. An overview of the tools and methods developed within the last 15 years is given and practical examples of the application of these analytical methods are presented." @default.
- W2131330491 created "2016-06-24" @default.
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- W2131330491 date "2007-07-07" @default.
- W2131330491 modified "2023-10-18" @default.
- W2131330491 title "Computational complexity and evolutionary computation" @default.
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- W2131330491 doi "https://doi.org/10.1145/1274000.1274112" @default.
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