Papers › A Literature Survey of Benchmark Functions For Global Optimization Problems

A Literature Survey of Benchmark Functions For Global Optimization Problems

19 Aug 2013arXiv:1308.4008archive 2025-07-28

Momin Jamil, Xin-She Yang

Test functions are important to validate and compare the performance of optimization algorithms. There have been many test or benchmark functions reported in the literature; however, there is no standard list or set of benchmark functions. Ideally, test functions should have diverse properties so that can be truly useful to test new algorithms in an unbiased way. For this purpose, we have reviewed and compiled a rich set of 175 benchmark functions for unconstrained optimization problems with diverse properties in terms of modality, separability, and valley landscape. This is by far the most complete set of functions so far in the literature, and tt can be expected this complete set of functions can be used for validation of new optimization in the future.

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AnHosu/opt-test-functions mentioned on GitHub report
MaximeRobeyns/OPTK mentioned on GitHubECL-2.0 report
kvoss/optobench mentioned on GitHubBSD-3-Clause report
luclaurent/optiGTest mentioned on GitHubGPL-3.0 report

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