New hard benchmark functions for global optimization

Understand

In this paper, we present some new unimodal, multimodal, and noise test functions to assess the performance of global optimization algorithms.

• All the test functions are multidimensional problems.
• The 2-dimension landscape of the proposed functions has been graphically presented in 3D space to show their geometry, however these functions are more complicated in dimensions greater than 3.
• To show the hardness of these functions, we have made an experimental study with some powerful algorithms such as CEC competition winners: LSHADE, MadDe, and LSHADE-SPACMA algorithms.