Real-Coded Genetic Algorithm for Rule-Based Flood Control Reservoir Management

Fi-John Chang and Li Chen

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 1998, vol. 12, issue 3, 185-198

Abstract: Genetic algorithms (GAs) have been fairly successful in a diverse range of optimization problems, providing an efficient and robust way for guiding a search even in a complex system and in the absence of domain knowledge. In this paper, two types of genetic algorithms, real-coded and binary-coded, are examined for function optimization and applied to the optimization of a flood control reservoir model. The results show that both genetic algorithms are more efficient and robust than the random search method, with the real-coded GA performing better in terms of efficiency and precision than the binary-coded GA. Copyright Kluwer Academic Publishers 1998

Keywords: binary-coded GA; flood control; fuzzy control; real-coded GA; reservoir optimization (search for similar items in EconPapers)
Date: 1998
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Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:12:y:1998:i:3:p:185-198

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DOI: 10.1023/A:1007900110595

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