سال انتشار: ۱۳۸۵

محل انتشار: هفتمین سمینار بین المللی مهندسی رودخانه

تعداد صفحات: ۸

نویسنده(ها):

Shafii – Department of Water Resources Eng, Moshanir Power Engineering Consultants
Bozorg Haddad – Department of Civil Eng, Iran University of Science and Technology
Afshar – Department of Civil Eng, Iran University of Science and Technology
Rahbar Basir – Department of Civil Eng, Iran University of Science and Technology

چکیده:

The frequency and severity of flooding has increased dramatically over recent years, and is now a World wide problem that requires increasing research and investment. Flood defense systems are designed and constructed to solve the problem of flooding and to protect lowlying areas. Design of a flood defense system is considerable from several aspects, such as economic, cultural and engineering, which is often the final stage for finding technical means to best accomplish the project goals. Over the years, researchers have been used riskbased design and optimization methods to obtain economic design of protection systems.Levee systems are one of flood defense systems that have been built for flood protection in numerous rivers, lakes and coasts in the world. Early flood levees usually were designed with scant quantitative analysis, but today economic design of a levee system for flood protection has been important. Construction costs of levee, the losses of land value sacrificed for floodway expansion (setback) and flood damages from inadequate channel capacity are the parameters used in economic design of flood levees. There have been several application of GAs to water resources problems in recent years. Genetic Algorithms has been developed into a powerful optimization approach. The primary objective of this paper is to introduce a new GA formulation in application to flood defense systems. The problem presented here is about optimization of levee setback. It has been demonstrated that presented formulation of GAs provide robust and acceptable solutions to the levees setback optimization problem.