A Visual-Based Approach for Evaluating Global Optimization Methods

In order to evaluate efficiency of some global optimization method or compare efficiency of different methods, it is necessary to select a set of test problems, define comparison measures, and, finally, choose a way of visual presentation of the computational results. In this paper, a wide set of test optimization problems is considered including a new global constrained optimization problem generator (GCGen). Main performance measures and comparative criteria of efficiency are presented. The ways of visual presentation of computational results are suggested.