# Plots

A contour of the function is presented below:

# Description and Features

• The function is not convex.
• The function is defined on 2-dimensional space.
• The function is non-separable.
• The function is differentiable.

# Input Domain

The function can be defined on any input domain but it is usually evaluated on $x_i \in [-100, 100]$ for $i=1, 2$.

# Global Minima

The function has one global minimum $f(\textbf{x}^{\ast}) = 0$ located at $\mathbf{x^\ast}=(0, 0)$.

# Implementation

An implementation of the Bohachevsky N. 2 Function with MATLAB is provided below.

The function can be represented in Latex as follows:

# References:

• Momin Jamil and Xin-She Yang, A literature survey of benchmark functions for global optimization problems, Int. Journal of Mathematical Modelling and Numerical Optimisation}, Vol. 4, No. 2, pp. 150–194 (2013), arXiv:1308.4008
• I. O. Bohachevsky, M. E. Johnson, M. L. Stein, “General Simulated Annealing for Function Optimization,” Technometrics, vol. 28, no. 3, pp. 209-217, 1986.