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Evolutionary Algorithms: Concepts, Designs, and Applications in Bioinformatics

Evolutionary Algorithms: Concepts, Designs, and Applications in Bioinformatics

Ka-Chun Wong
ISBN13: 9781522507888|ISBN10: 1522507884|EISBN13: 9781522507895
DOI: 10.4018/978-1-5225-0788-8.ch006
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MLA

Wong, Ka-Chun. "Evolutionary Algorithms: Concepts, Designs, and Applications in Bioinformatics." Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2017, pp. 111-137. https://doi.org/10.4018/978-1-5225-0788-8.ch006

APA

Wong, K. (2017). Evolutionary Algorithms: Concepts, Designs, and Applications in Bioinformatics. In I. Management Association (Ed.), Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications (pp. 111-137). IGI Global. https://doi.org/10.4018/978-1-5225-0788-8.ch006

Chicago

Wong, Ka-Chun. "Evolutionary Algorithms: Concepts, Designs, and Applications in Bioinformatics." In Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 111-137. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-0788-8.ch006

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Abstract

Inspired from nature, evolutionary algorithms have been proven effective and unique in different real world applications. Comparing to traditional algorithms, its parallel search capability and stochastic nature enable it to excel in search performance in a unique way. In this chapter, evolutionary algorithms are reviewed and discussed from concepts and designs to applications in bioinformatics. The history of evolutionary algorithms is first discussed at the beginning. An overview on the state-of-the-art evolutionary algorithm concepts is then provided. Following that, the related design and implementation details are discussed on different aspects: representation, parent selection, reproductive operators, survival selection, and fitness function. At the end of this chapter, real world evolutionary algorithm applications in bioinformatics are reviewed and discussed.

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