Dr. Ossama Abdelkhalik
Assistant Professor, Mechanical Engineering-Engineering Mechanics
One of the challenges for the future cyber-physical systems is
the exploration of large design spaces. Genetic algorithms
(GAs), which embody a simplified computational model of the
mutation and selection mechanisms of natural evolution, are
known to be effective for design optimization. However, the
traditional formulations are limited to choosing values for
a predetermined set of parameters within a given fixed
architecture.
Dr. Abdelkhalik's research explores techniques, based on the
idea of hidden genes, which enable GAs to select a variable
number of components, thereby expanding the explored design
space to include selection of a system’s architecture. Hidden
genetic optimization algorithms have a broad range of
potential applications in cyber-physical systems, including
automated construction systems, transportation systems,
micro-grid systems, and space systems.
In space systems, optimizing space missions’ trajectories is
of significant importance due to its impact on the space
mission cost and feasibility. To efficiently design a space
mission trajectory, the concept of hidden genes is developed
to compute, in an optimal sense, the number of planets’
fly-bys and the plan for propulsion system thrust usage so as
to optimize the overall space mission cost.
For more information, please visit Dr. Abdelkhalik's
website.
Recent publications
| 01 |
Hidden Genes Genetic Algorithm for Multi-Gravity-Assist Trajectories Optimization A. Gad, O. Abdelkhalik Journal of Spacecraft and Rockets, vol. 48, p. 629 (2011) |
| 02 |
Dynamic-Size Multiple Populations Genetic Algorithm for Multigravity-Assist Trajectories Optimization O. Abdelkhalik, A. Gad Journal of Guidance, Control and Dynamics, vol. 35, p. 520 (2012) |
| 03 |
Shape-Based Approximation of Constrained Low-Thrust Space Trajectories Using Fourier Series E. Taheri, O. Abdelkhalik Journal of Spacecraft and Rockets, vol. 49, p. 535 (2012) |
| 04 |
Hidden Genes Genetic Optimization for Variable-Size Design Space Problems O. Abdelkhalik Journal of Optimization Theory and Applications, vol. 156, p. 450 (2013) |
