Heuristic and meta-heuristic optimisation suite in Python
Project description
FreeLunch - Meta-heuristic optimisation suite for python
Basically a dump of useful / funny metaheurisitcs with a (hopefully) simpe interface
Feeling cute might add benchmarking later idk
There are literally so many implementations of all of these so... here's one more!
Features
Optimisers
Your favourite not in the list? Feel free to add it.
- Differential evolution
freelunch.DE
- Simulated Annealing
freelunch.SA
Benchmarking functions
Tier list: TBA
- N-dimensional Ackley function
- N-dimensional Periodic function
- N-dimensional Happy Cat function
- N-dimensional Exponential function
Usage
Install with pip (req. numpy).
pip install freelunch
Import and instance your favourite meta-hueristics!
import freelunch
opt = freelunch.DE(obj=my_objective_function, bounds=my_bounds)
Return best solution only.
quick_result = opt()
Return optimum after nruns
best_of_runs = opt(nruns = n)
Return best m
solutions in np.ndarray
best_m = opt(return_m = m)
Return json friendly dict with fun metadata!
full_output = opt(full_output = True)
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