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العنوان
Metaheuristic optimization algorithm for solving complex engineering problems /
المؤلف
Khatab, Mahmoud Radi Saleh.
هيئة الاعداد
باحث / محمود راضي صالح سعد خطاب
مشرف / محمد محمد المتولي الجمل
مشرف / عطاالله عطاالله محمد علي الشناوي
مشرف / أسماء حمدي ربيع
مناقش / عبدالمنعم محمد قوزع
مناقش / مجدى صللاح العزب صوان
الموضوع
Problem solving. Metaheuristics. Mathematical optimization.
تاريخ النشر
2024.
عدد الصفحات
online resource (79 pages) :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة
تاريخ الإجازة
1/1/2024
مكان الإجازة
جامعة المنصورة - كلية الهندسة - الرياضيات والفيزياء الهندسية
الفهرس
Only 14 pages are availabe for public view

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from 79

Abstract

”Optimization, a key branch of applied engineering mathematics, has emerged as an essential tool across various sectors such as industry, medicine, weather forecasting, and traffic design. It streamlines processes, ensuring that problems are solved in the most efficient way possible, saving time, effort, and money. This technique enhances decision-making and operational efficiency, proving indispensable in complex systems management.Given the significance of optimization and the substantial funding it receives, this field has become a fertile area for research and study. Researchers aim to develop optimal solutions for real-world problems. Numerous methods have been explored and refined in this quest, enhancing the practical impact and theoretical depth of optimization.In this thesis, two proposed techniques are represented, which can contribute to solving complex real-world engineering problems.The first proposed technique is a novel model representing the cooperation between two animals, which are the coyote and the honey badger, trying to mimic their natural biological behavior through pure and robust mathematical algorithms.The model was tested on standard benchmark functions and a real problem of designing a pressure vessel.The new model showed high competency against famous, well-known techniques.The second proposed technique enhances a well-known metaheuristic model, which is Grey Wolf Optimization (GWO).A new method for updating the agents’ positions is proposed, and when tested against the original technique, it demonstrated superior performance.”