Multi-Objective Genetic Algorithm Program - Running Demo Files Guide

To execute the demonstration files, run the SGALAB_demo_*.m scripts in MATLAB. The program features several key enhancements: 1) Multiple-Objective Genetic Algorithm implementations supporting VEGA (Vector Evaluated GA), NSGA (Non-dominated Sorting GA), NPGA (Niched Pareto GA), and MOGA (Multi-Objective GA) for Pareto-optimal solution finding 2) Expanded Traveling Salesman Problem operators including: - Crossover methods: PMX (Partially Mapped Crossover), OX (Order Crossover), CX (Cycle Crossover), EAX (Edge Assembly Crossover) - Advanced representation using Boolean matrix encoding for path optimization 3) Selection mechanism improvements featuring: - Truncation selection with threshold-based filtering - Tournament selection with configurable pool size - Stochastic universal sampling with probability distributions 4) Enhanced mutation operators supporting: - Binary encoding: single-point bit flipping - Integer/real-value encoding: single-point random perturbation - DNA permutation: sequence rearrangement operations 5) Advanced encoding/decoding schemes for: - Binary strings using direct mapping - Integer values with boundary constraints - Real numbers through normalization techniques - Messy encoding with variable-length chromosomes - Gray coding for smooth phenotype transitions - DNA permutation for biological sequence optimization To resolve plotting issues in version 4001, download the patch file and overwrite the existing plot functions in your installation directory. The fix addresses visualization bugs in Pareto front display and convergence curve plotting.