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Space Trajectories Optimization Using Variable-Chromosome-Length Genetic Algorithms, Ahmed H. Gad
Space Trajectories Optimization Using Variable-Chromosome-Length Genetic Algorithms, Ahmed H. Gad
Dissertations, Master's Theses and Master's Reports - Open
The problem of optimal design of a multi-gravity-assist space trajectories, with free number of deep space maneuvers (MGADSM) poses multi-modal cost functions. In the general form of the problem, the number of design variables is solution dependent. To handle global optimization problems where the number of design variables varies from one solution to another, two novel genetic-based techniques are introduced: hidden genes genetic algorithm (HGGA) and dynamic-size multiple population genetic algorithm (DSMPGA).
In HGGA, a fixed length for the design variables is assigned for all solutions. Independent variables of each solution are divided into effective and ineffective (hidden) genes. Hidden …