Mathematical Modeling Toolbox with Comprehensive Collection of Models

The Mathematical Modeling Toolbox provides diverse mathematical modeling implementations developed using MATLAB programming language. These models encompass linear programming (utilizing optimizations like simplex algorithm), nonlinear programming (with gradient-based solvers such as fmincon), dynamic programming (implementing Bellman's equation solutions), integer programming (branch-and-bound methods), graph theory (adjacency matrix operations), and difference equations (discrete-time system simulations). Each model includes configurable parameters and documented MATLAB functions (e.g., linprog for linear optimization, graphshortestpath for network analysis) to streamline problem-solving workflows. The toolbox enhances computational efficiency through vectorized operations and parallel computing capabilities where applicable. Supplementary tutorials demonstrate model customization through script examples and live-script workflows, while curated case studies illustrate real-world applications across engineering and research domains. This resource enables both students and professionals to accelerate mathematical problem-solving through standardized, reproducible code implementations.