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
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.