S. Muhammad Hossein Mousavi - Department of Computer Engineering, Bu Ali Sina University, Hamadan, Iran
Vladimir S.Myasnichenko - Department of Physics, Tver State University, Tver, Russia

In general terms, optimization means to improve the state of something; Having a function f(x) in optimization, we want to find an argument x whose relevant cost is optimum (usually minimum). The Test Functions, which known as Artificial Landscapes in Applied Mathematic, are utilized for assessing features of optimization algorithms such: convergence speed, accuracy, robustness and their total functionality. Single-objective optimization algorithms are the underlying basis to more sophisticated algorithms such: multi-objective optimization algorithms, niching, constrained optimization algorithms, etc. These functions are also used for testing of evolutionary algorithms (generally optimization). The aim of presenting this paper is to implement a sort of Test Function for single-objective optimization problems and validating of evolutionary algorithms. Acquired results indicate that, the proposed test function is able to perform optimization operation and validating evolutionary algorithms well.

Test Functions, Optimization Algorithms, Cost, Convergence, Evolutionary Algorithms