Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
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Floods are one of the major natural disasters that often threaten human lives and cause significant economic losses around the world. The history of mankind is filled with the stories of our struggles with floods to protect human races and to sustain the progression of our civilizations. Flood defense systems are designed and constructed to protect low-lying areas against flooding. Engineering design often is at the final stage for finding technical means to best accomplish the project goals. Over the years, risk-based design and optimization methods have proven to be useful tools to obtain economic design of protection systems. Levee systems have been built for flood protection in numerous rivers, lakes and coasts in the world over the long human history. Early flood levees usually were designed with scant quantitative analysis, relying primarily on occasional observations of flood stages and empirical judgments on required project scales. Economic design of a levee system for flood protection involves balancing costs of levee building (height), the losses of land value sacrificed for floodway expansion (setback) and flood damages from inadequate channel capacity. The application of GAs to water resources problems have been increased in recent years. The study of genetic algorithms (GAs) originated, and has developed into a powerful optimization approach. GAs have so far had very little applications in flood defense systems optimization. The primary objective of this paper is to explore the potential of alternative GA formulations in application to flood defense systems. The problem addressed here is about optimizing levee setback. The object has been to present GAs as a practical tool in levee design optimization. It has been demonstrated that GAs provide robust and acceptable solutions to the levees setback optimization problem.