Hi Daniele,
To effectively diagnose the issue, it would be beneficial to have the "entropy_calculated.txt" file. This file is crucial for reproducing the problem you have encountered.
Premature termination of a solver may occur when it is uncertain about the quality of the solution it has generated. This uncertainty may arise if the solver has converged at a local minimum without being able to confirm it, particularly if the first-order optimality measure hasn't fallen below the predefined optimality tolerance.
To verify the solution obtained, you might consider the following strategies:
1. Evaluate Surrounding Points: If you have a non-smooth objective function or non-smooth constraints, check nearby points to the solution.
2. Restart at the Last Solution: Run the algorithm again, starting from the point where the last solution was found.
3. Try Alternate Algorithms: Different algorithms may navigate the solution space differently and could avoid the pitfalls of the one you're currently using.
4. Adjust Tolerances: Modifying the tolerance settings can influence when the solver perceives convergence, potentially leading to a more accurate solution.
5. Rescale Your Problem: Scaling the problem can sometimes improve the numerical properties and lead to better optimization results.
6. Reexamine Surrounding Points: As mentioned earlier, investigating points near the solution can provide insights into the solution space of the function and the validity of the solution.
7. Modify Finite Difference Settings: If you're using numerical derivatives, changing the finite differencing scheme can affect the solver's trajectory.
8. Supply Analytical Gradients or Jacobian: Providing exact gradients or Jacobian can significantly improve the solver's ability to navigate the solution space.
9. Introduce a Hessian: If applicable, offering the Hessian matrix can enhance the solver's performance, particularly for second-order methods.
Refer to the following MATLAB documentation for further reference:
- When the Solver Might Have Succeeded: https://www.mathworks.com/help/optim/ug/when-the-solver-might-have-succeeded.html
- Constrained Nonlinear Optimization Algorithms: https://www.mathworks.com/help/optim/ug/constrained-nonlinear-optimization-algorithms.html
- fmincon: https://www.mathworks.com/help/optim/ug/fmincon.html
- First-Order Optimality Measure: https://www.mathworks.com/help/optim/ug/first-order-optimality-measure.html
Hope this helps!
Best regards,
Saarthak
