Parallel Multi-disciplinary Design Optimization of a Guided Flying Vehicle

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Darabi, Davoud | 2010

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 40128 (45)
University: Sharif University of Technology
Department: Aerospace Engineering
Advisor(s): Nobahari, Hadi
Abstract:
Multi-disciplinary design optimization (MDO) of a surface to air flying vehicle has been done in this research, on the basis of flight simulation. The MDO problem have five disciplines consists of aerodynamic, propulsion, guidance, control, and fire control. Multiple campaign scenarios are defined. The MDO problem has 31 design variables and two objective functions. The objective functions are flying vehicle weight and miss distance. A new meta-heuristic algorithm has been designed to solve multi-objective optimization problems. The new algorithm has been called Multi-objective Adaptive Real-coded Memetic Algorithm (MARCOMA). The MARCOMA can solve large-scale and multi-objective problems and it is derived by evolutionary algorithms. Also MARCOMA is capable of parallel processing. Parallel processing is provided by island model idea in the MARCOMA. Performances of the MARCOMA are compared by other meta-heuristic algorithms and the results have been shown that MARCOMA is successful. In the MARCOMA Pareto sulotions of the MDO problem have been produced where designers can choose an optimal solution based on their preferences and compromises
Keywords:
Memetic Algorithm ; Parallel Processing ; Optimal Design ; Multidisciplinary Optimization ; Multiobjective Optimization ; Simulation Based Design

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