Hi Gauri,
From what I understand, you are not able to see any variation on varying GA parameters while performing sensitivity analysis. There could be several reasons for that:
1) Single Optimization Variable: While having a single optimization variable might limit the complexity of the problem, it should still show some variation in results with different GA parameters.
2) Convergence: Your GA might be converging to the same solution every time, regardless of the parameters. This could be due to a well-defined problem with a clear global minimum.
3) Parameter Ranges: The ranges for your GA parameters might not be wide enough to show significant differences.
4) Problem Constraints: The constraints and bounds on your optimization variable might be too tight, leading to the same solution every time.
You can try performing the sensitivity analysis incorporating the following pointers which might be helpful.
- Wider Range of GA Parameters: Ensure that you are testing a sufficiently wide range of GA parameters.
- Multiple Runs: Run the GA multiple times for each set of parameters to account for the stochastic nature of GA.
- Record Detailed Metrics: Record not just the final objective value but also intermediate metrics like convergence rate, number of generations, and diversity of the population.
Hope this helps!
Best,
Umang
