Aerospace Knowledge and Technology Journal

Aerospace Knowledge and Technology Journal

Using genetic hybrid optimization algorithm and sequential quadratic programming for design optimization of a complex system

Document Type : Research Paper

Author
mohammad reza setayandeh
Assistant Professor, Department of Mechanical Engineering, Shahreza Campus, University of Isfahan, Iran.
Abstract
This paper aims to show the capability of hybrid optimization algorithms in finding the proper optimal plan for optimizing complex systems. So design optimization of an unmanned aerial vehicle has been presented as a complicated system by using multidisciplinary design optimization, genetic algorithm, and hybrid optimization algorithm. This study uses a hybrid optimization algorithm from a genetic algorithm as a global optimizer and from sequential quadratic programming as a local optimizer. The optimization problem of this study is a multi-objective design optimization problem in which the considered objective functions are the minimization of takeoff weight and cruise drag force. The considered constraints are related to the deflection of the control surface, stability, and handling quality specifications (damping coefficients, natural frequencies, and time constants). The proposed design optimization problem has been solved by using a hybrid optimization algorithm and genetic algorithm separately, and their results have been compared to each other. Although both optimal designs are acceptable, results show that the optimal design of the hybrid optimization algorithm is better than the optimal design of the genetic algorithm from an objective functions point of view. This issue shows the good performance of a hybrid optimization algorithm for design optimization of complex systems.
Keywords
Multidisciplinary design optimization
genetic algorithm
sequential quadratic programming
hybrid optimization algorithm
unmanned aerial vehicle
Subjects
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Aerospace Knowledge and Technology Journal
Volume 13, Issue 1
September 2024
Pages 147-167