This chapter delves into fundamental concepts of systems, modeling, simulation, and optimization, emphasizing systems science as an interdisciplinary field that investigates general attributes, dynamics, and behaviors common to various types of systems. Modeling is presented as a process of abstracting and simplifying real-world systems to represent their rules and interactions, enabling simulations that facilitate problem-solving and understanding. Optimization is highlighted as a critical tool for maximizing the performance of complex systems through deterministic and heuristic methods. A practical example includes the modeling of wind energy generation systems, incorporating turbine energy calculations and hybrid algorithms to address optimization challenges. Additionally, universal system properties such as entirety, composition, and internal and external organizations are detailed along with simulation techniques, including Monte Carlo, discrete-event, and continuous models. The chapter also explores optimization methods, particularly genetic algorithms, demonstrating the integration of heuristic and deterministic techniques to improve efficiency in multidisciplinary problems.