Three-dimensional aerodynamic shape optimization using genetic and gradient search algorithms

Norman F. Foster, George S. Dulikravich

Research output: Contribution to journalArticlepeer-review

77 Scopus citations


Two hybrid optimization methods used for preliminary aerodynamic design are introduced. The first is a gradient method based on Rosen's projection method and the method of feasible directions. The second technique is a genetic algorithm that uses elements of the Nelder-Mead simplex method to aid in search direction determination, as well as gradient methods to handle constrained problems. These methods are applied to three-dimensional shape optimization of ogive-shaped, star-shaped, spiked projectiles and lifting bodies in a hypersonic flow. Flowfield analyses are performed using Newtonian flow theory and, in one case, verified using a parabolized Navier-Stokes flow analysis algorithm. Three-dimensional geometrical rendering is achieved using a variety of techniques including beta splines from the computer graphics industry. In a comparison to the gradient-based method, the hybrid genetic algorithm is shown to be able to achieve impressive convergence on highly constrained problems while avoiding local minima.

Original languageEnglish (US)
Pages (from-to)36-42
Number of pages7
JournalJournal of Spacecraft and Rockets
Issue number1
StatePublished - 1997

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science


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