Multi-Objective Genetic Algorithm General Programming Package

The Multi-Objective Genetic Algorithm General Programming Package is a comprehensive toolkit designed for solving complex multi-objective optimization problems. It provides a suite of advanced functions and algorithmic implementations that enable users to efficiently address multi-objective optimization challenges. This package includes customizable genetic algorithm components such as chromosome encoding/decoding methods, selection operators (tournament, roulette wheel), crossover techniques (single-point, uniform), and mutation operations. Through this programming package, users can easily construct and optimize multi-objective genetic algorithms tailored to various complex problem domains. The toolkit implements key multi-objective optimization algorithms including NSGA-II (Non-dominated Sorting Genetic Algorithm II) and SPEA2 (Strength Pareto Evolutionary Algorithm 2), featuring Pareto-based ranking systems and crowding distance calculations for maintaining population diversity. The package also offers extensive analytical tools and evaluation functions for performance assessment, including hypervolume indicators, generational distance metrics, and convergence analysis utilities. These tools support comprehensive algorithm benchmarking and result visualization through plotting functions for Pareto fronts and convergence curves. Whether in academic research or practical applications, this general programming package serves as a powerful and practical tool that helps users achieve superior optimization results through its modular architecture, extensive documentation, and cross-platform compatibility.