Abolfazl Shirazi defenderá su tesis doctoral el jueves 11 de marzo
- Debido a la situación causada por la pandemia de COVID-19 la defensa se llevará a cabo en línea y será retransmitida en directo
Abolfazl Shirazi se licenció en Ingeniería Aeroespacial en 2010 y en 2012 obtuvo un máster en en el mismo campo.
En 2016 se unió al Basque Center for Applied Mathematics – BCAM como estudiante de doctorado dentro de la línea de investigación de Machine Learning dentro del grupo de Data Science en el marco de Beca La Caixa
Su tesis doctoral, Efficient Meta-heuristics for Spacecraft Trajectory Optimization, ha sido supervisada por Prof. Josu Ceberio (UPV/EHU) y Prof. Jose Antonio Lozano (BCAM).
Debido a la situación causada por la pandemia de COVID-19 la defensa se llevará a cabo en línea y será retransmitida en directo a través de la plataforma BB-Collaborate. Tendrá lugar el jueves 11 de marzo a las 12:00 horas, y los usuarios podrán seguirla en directo a través del siguiente enlace: https://eu.bbcollab.com/guest/b4716b035afe4c6980035afec493440b
En nombre de todos los miembros de BCAM, nos gustaría desear a Abolfazl la mejor de las suertes en la defensa de su tesis.
PhD thesis Title:
Efficient Meta-heuristics for Spacecraft Trajectory Optimization
Abstract:
Spacecraft trajectory optimization is one of the challenging subjects in astrodynamics. Cutting-edge technology for orbital maneuvers of the space vehicles turns this subject into a matter of interest for the aerospace community, as it has a major impact in space mission analysis and design. At the same time, rapid development of computational capabilities allows computer science areas such as artificial intelligence to get involved with real-world problems. This dissertation was an effort to make this connection and to develop novel meta-heuristics with high efficiency, concentrating on the adaptive behavior of the algorithms relative to the characteristics that describe the space orbit transfer mission. To this end, first, a comprehensive review was carried out, evaluating all state-of-art techniques and methods to deal with spacecraft trajectory optimization problems. Then, long-range and short-range space rendezvous transfers were chosen as two general target problems to be tackled in this dissertation. Consequently, two algorithms were developed for long-range and short-range space rendezvous missions respectively. In the development of these algorithms, special attention has been paid to the discovery of the features of the problems and connecting them to the parameters of the algorithms. The algorithms were mainly developed relying on probabilistic basis. Conducted experiments confirm the robustness and the efficiency of the proposed algorithms in tackling different problems. Besides the algorithms, a simulation software is also developed to provide a framework for the visualizing of space trajectories.
