Missile trajectory optimization using a modified ant colony algorithm

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.