Open Access
Table C.1
Overview and comparison of different algorithms
| Algorithm | Nmodels | Advantage | Disadvantage |
|---|---|---|---|
| Grid scan with local minimization | 107 | Considers more than only one solution, can be reused for other sources, few controllable parameters | Computationally expensive, drastic increase in computing cost with the increase of model parameters |
| Genetic algorithm | 105−106 | Able to cover large part of parameter space, overcomes local minima | Only one solution, sensitive to setting of algorithm parameters |
| CMA-ES | 105 | Able to cover large part of parameter space, overcomes local minima, self-adaption of algorithm parameters | Only one solution |
| Minuit (simplex + migrad) | 103 | Computationally inexpensive, few controllable parameters | May be sensitive to local minima, only one solution, sensitive to the choice of initial point |
| MCMC (ensemble sampler) | 105 | Provides parameter distributions | Sensitive to the choice of initial point and algorithm parameters |
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