Dynamic-Size Multiple Population Genetic Algorithms
Ossama O. Abdelkhalik · 2020
This chapter presents the method with several examples on its implementation to the interplanetary trajectory optimization problem. To overcome this problem, the concept of dynamic-size multiple population genetic algorithms (DSMPGA) is introduced. The concept of the DSMPGA is to create an initial population that consists of subpopulations. The resulting sub-population is considered as an initial population in the next stage. The population is divided into 14 sub-populations. The solution obtained using the DSMPGA tool in this paper has one swing by Venus and one DSM in each leg, 0.296 and 0.626 km/s, respectively. A minimum-cost solution trajectory for the Earth-Jupiter mission is addressed in reference. The DSMPGA tool developed in this paper is able to find automatically the known swing-by sequence, EVEJ, for the Jupiter mission in 2016.