Visualization of evolutionary algorithms - set of standard techniques and multidimensional visualization
Hartmut Pohlheim · 1999
Evolutionary algorithms work in an algorithmically simple manner but produce a vast amount of data. The extraction of useful information to gain further insight into state and course of the algorithm is a non-trivial task. In this paper we present a set of standard visualization techniques for different data types and time frames of the evolutionary algorithm. The methods were selected according to their usefulness for real world applications, and tested during the solution of some complex real world optimization problems. Additionally, multidimensional scaling as a technique for the presentation of high-dimensional data with standard visualization techniques is presented. We demonstrate the use of this technique for the visualization of the "path through the search space" of the best individuals during an optimization run, and for the comparison of multiple runs regarding the variables of individuals and multi criteria objective values ("path through solution space").