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العنوان
Neural network and genetic algorithm for solving multi-objective optimization problems and its applications in research reactor /
المؤلف
Ibrahim, Wesam Zakaria Awwad.
الموضوع
Algorithms. Neural computers - Design and construction.
تاريخ النشر
2009.
عدد الصفحات
147 p. :
الفهرس
Only 14 pages are availabe for public view

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from 163

Abstract

. The purpose of this thesis is to present an approach to optimize some of Reactor problem such as, the Fuel Element Plate, in which every target is considered as a separate objective to be optimized. Which, Multi objective optimization is a powerful tool for resolving conflicting objectives in engineering design and numerous other fields. The Fuel Element Plate is designed with a view to improve reliability and lifetime and it is one of the most important elements during the shut down. In this thesis, we present a conceptual design approach for fuel element plate, in conjunction with a genetic algorithm to obtain a Fuel plate that maximizes a fitness value to optimizing the safety design of the fuel plate.
Also, the Chimney Water Injection System of Egypt Second Research Reactor also, every target is considered as a separate objective to be optimized. One approach to solving multi objective optimization problems is the non-dominated sorting genetic Algorithm and we applied it in regarding the choice of the time intervals for the periodic testing of the components of the Chimney Water Injection System “CWIS” of the 22 MW open pool Multipurpose Reactor ”MPR” at the Atomic Energy Authority, Cairo- Egypt.