MOEA toolbox for computer aided multi-objective optimization

This paper presents a comprehensive Graphical User Interface (GUI) based MOEA Toolbox that implements Multi-Objective Evolutionary Algorithm (MOEA). The toolbox incorporates Pareto cost assignment scheme and other complementary features of hard constraint specification for constraint handling, dynamic population size, fuzzy boundary local perturbation with interactive local fine-tuning, a novel switching preserved strategy and convergence representation for multi-objective optimization. The user only needs a little programming knowledge to write the model file. Other aspects of the simulation like the settings, process monitoring and results analysis are performed on user-friendly and user-interactive GUI windows with easy-to-understand on-line help files. The MOEA Toolbox´s performance in a benchmark problem and an actual application has been presented as a demonstration of the toolbox´s capabilities