Abstract The blackbox optimization benchmarking (bbob) test suite comprises 24 noiseless single-objective test functions. BBOB is one of the most widely used test suites to evaluate and compare the performance of blackbox optimization algorithms. Each benchmark function is provided in dimensions [2, 3, 5, 10, 20, 40] with 110 instances.
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].
Abstract The bbob-biobj test suite was created by combining existing 55 noiseless single-objective test functions. bbob-biobj (and its extension, bbob-biobj-ext) has in total of 92 (= original 55 + additional 37) bi-objective functions. Each benchmark function is provided in dimensions [2, 3, 5, 10, 20, 40] with 15 instances. In this package, all the 92 functions are available. 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.
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].
Abstract The blackbox optimization benchmarking noisy (bbob-noisy) test suite comprises 30 noisy test functions. Each benchmark function is provided in dimensions [2, 3, 5, 10, 20, 40] 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 [101, 130]. dimension: Dimension of the benchmark function.
Abstract This package provides a wrapper of the COCO experiments libarary’s bbob-constrained test suite.
APIs class Problem(function_id: int, dimension: int, instance_id: int = 1) function_id: ID of the bbob-constrained benchmark function to use. It must be in the range of [1, 54]. dimension: Dimension of the benchmark function. It must be in [2, 3, 5, 10, 20, 40]. instance_id: ID of the instance of the benchmark function. It must be in the range of [1, 15].
Abstract This package provides test suites for the C-DTLZ problems (Jain & Deb, 2014), a constrained version of the DTLZ problems (Deb et al., 2001). The DTLZ problems are a set of continuous multi-objective optimization problems consisting of seven types, each supporting a variable number of objectives and variables. The C-DTLZ problems extend the DTLZ problems by adding various types of constraints to some of them. The objective functions are wrapped from the DTLZ test suite in optproblems, while the constraint components are implemented separately according to the original paper (Jain & Deb, 2014).
Abstract This package provides a wrapper of the optproblems library’s DTLZ test suite, which consists of 7 kinds of continuous problems with variadic objectives and variables. For the details of the benchmark problems, please take a look at the original paper (Deb et al., 2001) in the reference section.
APIs class Problem(function_id: int, n_objectives: int, dimension: int, k: int, **kwargs: Any) function_id: Function ID of the DTLZ problem in [1, 7].
Abstract This package provides a wrapper of the optproblems library’s WFG test suite, which consists of 9 kinds of continuous problems with variadic objectives and variables. For the details of the benchmark problems, please take a look at the original paper (Huband et al., 2006) in the reference section.
APIs class Problem(function_id: int, n_objectives: int, dimension: int, k: int | None = None, **kwargs: Any) function_id: Function ID of the WFG problem in [1, 9].