The use of computer programs driven by genetic algorithms has become an increasingly popular method for optimizing engineering designs. This paper focuses on the modeling and optimization of liquid-rocket-enginepropelled missiles with a computer program that is composed of a series of codes that simulate the performance of liquid-propelled rockets andare controlledby a genetic algorithm.Because the entiremissile design is considered, the complete system performance must be modeled accurately and efficiently. The methodology described in this paper has been extended to both the preliminary design and reverse-engineering of liquid-propelled missiles. The performance model has been validated against the performance of a liquid-propelled missile and the results are provided. Two different fast-aerodynamic-prediction codes are used and their results are compared. A complete preliminary design of a liquid-propelled missile system is considered with a variety of goals and constraints. Results from the preliminary design optimization are also shown and discussed in detail.

Genetic-Algorithm Optimization of Liquid-Propellant Missile Systems

Design Tool Development for Liquid Propellant Missile Systems

A modified ant colony optimization (ACO) algorithm is applied to a single-stage solid missile design problem involving six degrees of freeedom (6-DOF) flight trajectory modeling. A local search procedure is also integrated with the algorithm, adding a search intensification ability that compliments the ability of ACO to thoroughly explore a solution space. The goal of this work is to evaluate the effectiveness of the ant colony optimization scheme by comparing its solution output quality with those of other, well-known optimization methods. Performance is based on solution “fitness”, or how closely each solution matches a specific set of performance objectives, as well as the number of calls to the objective function that are required in order to reach that solution. Additionally, an important performance criterion is to determine each algorithm0s capabilities of finding, not only a single quality solution to a design problem, but also a diverse set of additional, near-optimal solutions. The results of this study demonstrate that the modified ACO algorithm is a viable candidate as a high-performance optimization method, while the added local search method may or may not be a worthwile addition for the attempted optimization problem.

Missile trajectory optimization using a modified ant colony algorithm

Aerospace design optimization using a compound repulsive particle swarm

A modified ant colony optimization (ACO) algorithm is applied to a set of solid-rocketmotor and single-stage solid missile design problems. A local search procedure is also integrated with the algorithm, adding a search intensification ability that compliments the ability of ACO to thoroughly explore a solution space. The goal of this work is to evaluate the effectiveness of the ant colony optimization scheme by comparing its solution output quality with those of other, well-known optimization methods. Performance is based on solution “fitness”, or how closely each solution matches a specific set of performance objectives, as well as the number of calls to the objective function that are required in order to reach that solution. Additionally, an important performance criterion is to determine the algorithm′s capabilities of finding, not only a single quality solution to a design problem, but also a diverse set of additional, near-optimal solutions.

Ant Colony Optimization : An Alternative Heuristic for Aerospace Design Applications

: This report is intended to be a users manual for a computer program called AERODSN, which estimates the stability coefficients of typical missile configurations with wings or tail fins or both. The Mach range is from zero to approximately 4.0. The roll orientation is zero (plus configuration). Wings and tails must be in line. Control deflections are allowed. A limited amount of body alone experimental data is included (ogive cylinder or cone cylinder); however, body alone tables can be input if desired. A conical boattail segment can be added. This program does not predict drag. Static stability and damping derivatives at zero angle of attack are predicted. (Author)

W D Washington

Papers

Computer Program for Estimating Stability Derivatives of Missile Configurations - Users Manual.