Local search seems to perform differently for single-objective test functions and programmable problems

[gkronber]

Reproduce:

1. Run local search or simulated annealing with 10-dim Rastrigin (test function)
2. Create programmable problem and implement evaluation function for Rastrigin
3. Implement neighborhood method (add Gaussian to one element) (check additive move generator in test functions)
4. Run local search or simulated annealing --> completely different convergence behaviour

Especially alarming is the facts at local search always converges to the global optimum for the multi-modal Rastrigin function (?!)

[abeham]

I can't reproduce this behavior. Both LS on a programmable problem as well as on the test function implementation converge to about Xe-05 within 1000 iterations and 100 samples.

Please be so kind and attach the hl file with your programmable problem. I suspect you used different bounds (original bounds are [-5.12 ; 5.12 ] for every dimension).

Rastrigin, while highly multi-modal, is still a separable problem.

[abeham]

programmable problem implementing the 10d rastrigin test function

[gkronber]

Thanks for testing this and for preparing the demo problem implementation.