Added GRSA implementation and tests

[erssylmz12]

📑 Description

This pull request adds the General Relativity Search Algorithm (GRSA) to the physics_based optimizer family in Mealpy.

GRSA is a physics-inspired metaheuristic that models particle movement using
time-like, space-like, and null-like geodesic components together with a
relativistic step-length factor and a small mutation operator for diversity.

Changes included

• Added mealpy/physics_based/GRSA.py — implementation of DevGRSA and OriginalGRSA
• Added tests/physics_based/test_grsa.py — unit tests for correctness and API compatibility
• Updated mealpy/physics_based/__init__.py — exported OriginalGRSA
• Updated README.md — added GRSA entry to the optimizer classification table

Key Hyperparameters

• w_max, w_min — step-length schedule
• k_g — relativistic factor scaling
• mutation_rate — diversity / exploration control

✅ Checks

• My pull request adheres to the code style of this project
• My code follows Mealpy’s conventions (self.generator, correct_solution, etc.)
• I have added tests for the new optimizer
• All the tests have passed
• I have updated the documentation / README where required

ℹ Additional Information

Reference:
Beiranvand, H., & Rokrok, E. (2015). General Relativity Search Algorithm: A Global Optimization Approach. International Journal of Computational Intelligence and Applications.

Happy to revise based on review feedback 👍