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Abolfazl Shirazi


I am a Postdoctoral Researcher at BCAM - Basque Center for Applied Mathematics. In 2016, I was awarded the La Caixa Fellowship Grant for my doctoral studies and in 2021 I obtained my Ph.D. degree with “Sobresaliente Cum Laude” distinction award from the University of the Basque Country UPV/EHU. My research interests are Astrodynamics and Machine Learning and my activities mainly involve spacecraft trajectory optimization, evolutionary computations, space dynamics and control, numerical simulation, orbital mechanics, meta-heuristics, and software development for space simulation.


Orbital Mechanics

Orbit Propagation
Orbital Maneuvers
Trajectory Optimization
Interplanetary Transfers

Machine Learning

Continuous Optimization
Evolutionary Algorithms

Spacecraft Dynamics

Spacecraft Guidance
Satellite Attitude Control
Space Mission Analysis
G.N.C Systems


3D Visualization
Software Development
3D Design & Modeling
Realtime Simulation

Featured Articles

An evolutionary discretized Lambert approach for optimal long-range rendezvous considering impulse limit
Shirazi, A., Ceberio, J. and Lozano, J.A.
Aerospace Science and Technology 94 (2019): 105400
DOI: 10.1016/j.ast.2019.105400
In this paper, an approach is presented for finding the optimal long-range space rendezvous in terms of fuel and time, considering limited impulse. In this approach, the Lambert problem is expanded towards a discretized multi-impulse transfer. Taking advantage of an analytical form of multi-impulse transfer, a feasible solution that satisfies the impulse limit is calculated. Next, the obtained feasible solution is utilized as a seed for generating individuals for a hybrid self-adaptive evolutionary algorithm to minimize the total time, without violating the impulse limit while keeping the overall fuel mass the same as or less than the one associated with the analytical solution. The algorithm eliminates similar individuals and regenerates them based on a combination of Gaussian and uniform distribution of solutions from the fuel-optimal region during the optimization process. Other enhancements are also applied to the algorithm to make it auto-tuned and robust to the initial and final orbits as well as the impulse limit. Several types of the proposed algorithm are tested considering varieties of rendezvous missions. Results reveal that the approach can successfully reduce the overall transfer time in the multi-impulse transfers while minimizing the fuel mass without violating the impulse limit. Furthermore, the proposed algorithm has superior performance over standard evolutionary algorithms in terms of convergence and optimality.

Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions
Shirazi, A., Ceberio, J. and Lozano, J.A.
Progress in Aerospace Sciences 102 (2018): 76-98
DOI: 10.1016/j.paerosci.2018.07.007
This article is a survey paper on solving spacecraft trajectory optimization problems. The solving process is decomposed into four key steps of mathematical modeling of the problem, defining the objective functions, development of an approach and obtaining the solution of the problem. Several subcategories for each step have been identified and described. Subsequently, important classifications and their characteristics have been discussed for solving the problems. Finally, a discussion on how to choose an element of each step for a given problem is provided.

  • ashirazi@bcamath.org
  • ashirazi@homasim.com
  • Tel: +34 946 567 842
  • Fax: +34 946 567 843
    Mazarredo, 14, 48009
    Bilbao, Spain
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