Section: New Results

A large-scale optimization testbed for the COCO framework

We have finalized a large scale testbed built to model well-known difficulties in continuous optimization and to test the scaling behavior of algorithms. It contrasts with current test suites used for benchmarking solvers.

The test suite contains 24 single-objective functions in continuous domain and extends the well-known single-objective noiseless bbob test suite. A core contribution is to reduce the computational demand of the orthogonal search space transformations, that appear in the bbob test suite, while retaining some desired properties using previously introduced permuted block diagonal orthogonal matrices.

The paper discusses the implementation details, particularly the normalization and scaling to obtain backwards compatibility with the bbob test suite. Additionally, a guide for using the test suite within the COCO platform, as well as a description of the postprocessed output is presented [12].