Abstract
The blackbox optimization benchmarking largescale (bbob-largescale) test suite comprises high-dimensional 24 noiseless single-objective test functions. Each benchmark function is provided in dimensions [20, 40, 80, 160, 320, 640] with 15 instances. Please refer to the paper for details about each benchmark function.
APIs
class Problem(function_id: int, dimension: int, instance_id: int = 1)
function_id
: ID of the bbob benchmark function to use. It must be in the range of[1, 24]
.dimension
: Dimension of the benchmark function. It must be in[20, 40, 80, 160, 320, 640]
.instance_id
: ID of the instance of the benchmark function. It must be in the range of[1, 15]
.
Methods and Properties
search_space
: Return the search space.- Returns:
dict[str, optuna.distributions.BaseDistribution]
- Returns:
directions
: Return the optimization directions.- Returns:
list[optuna.study.StudyDirection]
- Returns:
__call__(trial: optuna.Trial)
: Evaluate the objective function and return the objective value.- Args:
trial
: Optuna trial object.
- Returns:
float
- Args:
evaluate(params: dict[str, float])
: Evaluate the objective function given a dictionary of parameters.- Args:
params
: Decision variable like{"x0": x1_value, "x1": x1_value, ..., "xn": xn_value}
. The number of parameters must be equal todimension
.
- Returns:
float
- Args:
The properties defined by cocoex.Problem are also available such as number_of_objectives
.
Installation
Please install the coco-experiment package.
pip install -U coco-experiment
Example
import optuna
import optunahub
bbob = optunahub.load_module("benchmarks/bbob-largescale")
sphere640d = bbob.Problem(function_id=1, dimension=640, instance_id=1)
study = optuna.create_study(directions=sphere640d.directions)
study.optimize(sphere640d, n_trials=20)
print(study.best_trial.params, study.best_trial.value)
Reference
Elhara, O., Varelas, K., Nguyen, D., Tusar, T., Brockhoff, D., Hansen, N., & Auger, A. (2019). COCO: the large scale black-box optimization benchmarking (BBOB-largescale) test suite. arXiv preprint arXiv:1903.06396.
- Package
- benchmarks/bbob_largescale
- Author
- Optuna team
- License
- MIT License
- Verified Optuna version
- 4.1.0
- Last update
- 2025-01-21