Determining the optimal solution for a problem, program, or research proposal is a significant and sometimes time-consuming objective. This becomes particularly evident when classical optimization techniques lose their effectiveness, propelling researchers towards new optimization algorithms. The reason behind this is the very high speed, coupled with desirable accuracy and an approximation very close to the optimal solution, which is accessible through such methods. Due to the importance of optimization and its extensive application across all sciences, numerous studies have been conducted to propose optimization algorithms, and there is a close competition in the scientific community in this regard. Given the significance of optimization, this educational collection introduces an efficient and novel optimization algorithm (published in 2022). Alongside information about this algorithm and guidance on its implementation, the collection presents ten unconstrained problems and ten constrained problems, from coding to optimization stages. After completing this course, you will be capable of fully implementing your problem based on the presented technique.

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  • 4 hours and 58 minutes of instructional videos
  • Programming and implementation tutorials
  • Explanation of problem-solving using codes
  • Detailed presentation of the TS 2022 algorithm
  • Simple editing capability for any type of problem
  • Coding and solving 10 unconstrained problems
  • Coding and solving 10 constrained problems


  • Part 1: Introduction to Optimization
  • Part 2: The Transit Method in Astrophysics
  • Part 3: Optimization Algorithm for Transit Search
  • Part 4: Implementing the TS Algorithm in MATLAB 2020
  • Part 5: Coding and Solving 10 Unconstrained Problems in MATLAB
  • Part 6: Coding and Solving 10 Constrained Problems in MATLAB


Dr. Masoomeh Mirrashid
Research Fellow (Postdoctoral)

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