Evo-Panel: Dynamic Visualization Tool for Optimization Process

Evolutionary algorithms (EAs) are efficient computational intelligence (CI) techniques for solving complex optimization problems in different areas. Explainable artificial intelligence (XAI) has recently emerged as a popular research topic as people are increasingly attempting to know the manner in which AI algorithms attain results. In this context, understanding and analyzing the optimization processes of EAs to effectively enhance their performance are crucial and challenging tasks. Most traditional visualization methods focus on dimensionality reduction, visualization of the fitness landscape and the optimization process for a particular algorithm. This study represents the first attempt at establishing a comprehensive dynamic visualization tool, Evo-Panel, that can directly and flexibly illustrate the detailed procedures of different optimization algorithms in solving numerical benchmark functions. The objective is to help users identify the influence of the design formulas, operations, and parameters on the capabilities and performances of the algorithms. Using Evo-Panel, users can trace each movement, observe the process in an intuitive manner, and interpret the processes related to EAs, which are important to XAI. Moreover, Evo-Panel can be used to perform a comparative analysis to illustrate the differences between algorithms. Results of case studies demonstrate that the use of Evo-Panel can allow professors to explain optimization algorithms in a visually interesting manner and facilitate the students' understanding of EAs. The tool can promote CI-related education from teaching and learning perspectives. Furthermore, researchers can use it to obtain information for analysis, facilitate debugging, verify design ideas, gain insights into the process, and enhance the design of EAs.