Solid Rocket Motor Design Using a Modified Ant Colony Optimization Metaheuristic with Local Search Capability

A modified ant colony optimization (ACO) metaheuristic is integrated with a local search procedure to produce an algorithm that combines the ability of ACO to locate global optimum solutions with the local search intensification ability of Nelder and Mead’s simplex method to efficiently locate local optima within the solution space. Optimizer performance is evaluated according to two criteria : (1) “fitness function” accuracy, or how closely solutions are able to match a given “objective function”, and (2) convergence speed, which is based on how many calls to this function are required in order to reach the optimal solution found by the algorithm. Design of a star grain solid rocket motor (SRM) to match a specified chamber pressure vs. time curve is used as the objective function. The SRM performance model, supporting background information, algorithm details, and test results are described and future work possibilities are discussed.

[1]  Marco Dorigo,et al.  Ant colony optimization for continuous domains , 2008, Eur. J. Oper. Res..

[2]  Roy J. Hartfield,et al.  Hybrid Particle Swarm-Pattern Search Optimizer for Aerospace Propulsion Applications , 2010 .

[3]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[4]  Robert Hooke,et al.  `` Direct Search'' Solution of Numerical and Statistical Problems , 1961, JACM.

[5]  Ronald L. Nichols,et al.  Solid rocket propulsion , 1991 .

[6]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[7]  Douglas James Bayley.  Design Optimization of Space Launch Vehicles Using a Genetic Algorithm , 2007 .

[8]  Roy J. Hartfield,et al.  Aerospace design optimization using a steady state real-coded genetic algorithm , 2008, Appl. Math. Comput..

[9]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[10]  Rhonald M. Jenkins,et al.  Analytical Methods for Predicting Grain Regression in Tactical Solid-Rocket Motors , 2004 .

[11]  Marco Dorigo,et al.  Ant colony optimization , 2006, IEEE Computational Intelligence Magazine.

[12]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[13]  Luca Maria Gambardella,et al.  An Ant Colony Optimization Approach to the Probabilistic Traveling Salesman Problem , 2002, PPSN.

[14]  Roy J. Hartfield,et al.  Genetic-Algorithm Optimization of Liquid-Propellant Missile Systems , 2009 .

[15]  T. Stützle,et al.  A Review on the Ant Colony Optimization Metaheuristic: Basis, Models and New Trends , 2002 .

[16]  J. Deneubourg,et al.  Self-organized shortcuts in the Argentine ant , 1989, Naturwissenschaften.

[17]  Roy J. Hartfield,et al.  Solid Rocket Motor Performance Matching Using Pattern Search/Particle Swarm Optimization , 2011 .