Multidisciplinary design optimization of a reentry vehicle using genetic algorithm
Abstract
Purpose
The purpose of this paper is the optimal design of a reentry vehicle configuration to minimize the mission cost which is equal to minimize the heat absorbed (thermal protection system mass) and structural mass and to maximize the drag coefficient (trajectory errors and minimum final velocity).
Design/methodology/approach
There are two optimization approaches for solving this problem: multiobjective optimization (lead to Pareto optimal solutions); and single‐objective optimization (lead to one optimal solution). Single‐objective genetic algorithms (GA) and multiobjective Genetic Algorithms (MOGA) are employed for optimization. In second approach, if there are n objectives (n+1) GA run is needed to find nearest point (optimum point), which leads to increase the time processing. Thus, a modified GA called single run GA (SRGA) is presented as third approach to avoid increasing design time. It means if there are n objectives, just one GA run is enough.
Findings
Two multi module function – Ackley and bump function – are selected for examination the third approach. Results of MOGA, GA and SRGA are presented which show SRGA approach can find the nearest point in much shorter time with acceptable accuracy.
Originality/value
GA, MOGA and SRGA approaches are applied to multidisciplinary design optimization of a reentry vehicle configuration and results show the efficiency of SRGA in complex design optimization problem.
Keywords
Citation
Nosratollahi, M., Mortazavi, M., Adami, A. and Hosseini, M. (2010), "Multidisciplinary design optimization of a reentry vehicle using genetic algorithm", Aircraft Engineering and Aerospace Technology, Vol. 82 No. 3, pp. 194-203. https://doi.org/10.1108/00022661011075928
Publisher
:Emerald Group Publishing Limited
Copyright © 2010, Emerald Group Publishing Limited