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- W2012132549 abstract "Lucasius, C.B. and Kateman, G., 1993. Understanding and using genetic algorithms. Part 1. Concepts, properties and contexts. Chemometrics and Intelligent Laboratory Systems, 19: 1–33. Genetic algorithms are search algorithms founded upon the principles of natural evolution laid down by Darwin. They turn out to be competitive for a certain class of problems — complex large-scale problems, as a rule. Among the favorable properties of genetic algorithms are: efficiency, robustness and versatility. A less favorable property of genetic algorithms is the imprecision as a result of the noise used by the method. This tutorial consists of two parts which treat a variety of key issues concerning genetic algorithms. The first part emphasizes the principles underlying genetic algorithms, their search characteristics and the broader perspective in which they fit. This serves as a general, comprehensive introduction. Starting from the first part, the second part of this tutorial elaborates on practical issues such as representation, configuration and hybridization with other techniques. Thereby, some hands-on information is provided, so that common pitfalls can be avoided in using a methodology that exhibits its full power only when handled according to the principles it is based upon." @default.
- W2012132549 created "2016-06-24" @default.
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- W2012132549 date "1993-05-01" @default.
- W2012132549 modified "2023-10-14" @default.
- W2012132549 title "Understanding and using genetic algorithms Part 1. Concepts, properties and context" @default.
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- W2012132549 doi "https://doi.org/10.1016/0169-7439(93)80079-w" @default.
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