Self Organizing Maps (SOM) for Design Selection in Multi-Objective Optimization using modeFRONTIER
Self Organizing Maps (SOM) has evolved as a very useful visualization and data analysis tool for high dimensional data. Visualization and analysis of Pareto data for multi-objective optimization problems with more than three objectives is also a challenge. This paper will investigate the application of SOM for visualization and design selection for multi-objective Pareto data. The SOM is applied to investigate the spread of Pareto front as well as to investigate trade-off between objectives. The visualization and selection strategy is applied to mathematical test problem to explain the concept. Later it is also applied to real world automotive design problem of engine optimization.