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Aerospace design optimization using a steady state real-coded genetic algorithm
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AI
DOI：10.1016/j.amc.2011.07.038.png)
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Abstract
En 中文
This study demonstrates the advantages of using a real coded genetic algorithm (GA) for aerospace engineering design applications. The GA developed for this study runs steady state, meaning that after every function evaluation the worst performer is determined and that worst performer is then thrown out and replaced by a new member that has been evaluated. The new member is produced by mating two successful parents through a crossover routine, and then mutating that new member. For this study three different preliminary design studies were conducted using both a binary and a real coded GA including a single stage solid propellant missile systems design, a two stage solid propellant missile systems design and a single stage liquid propellant missile systems design. (C) 2011 Elsevier Inc. All rights reserved.
Keywords:
Aerospace
Optimization
Rocket propulsion
Genetic algorithm
Real coded genetic algorithm
Steady state genetic algorithm
Journal
IF:
3.4
Papers:
2.3W
Citations:
3.3W
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