In modern industrial operations, complexity is increasing as organizations manage multiple interconnected systems that must work together seamlessly. Traditional optimization approaches often focus on improving individual components, but in reality, industries operate as interdependent networks where changes in one system influence the performance of others. This is where System of Systems Engineering (SoSE) emerges as a transformative approach, enabling industries to optimize large-scale, interconnected systems holistically rather than in isolation.

In an increasingly data-driven world, industries face optimization problems that are too complex for traditional mathematical methods to address. Whether it is scheduling production, optimizing supply chains, or managing logistics, the complexity of these challenges requires advanced problem-solving techniques. Metaheuristic algorithms have emerged as a powerful solution, enabling industries to identify near-optimal answers to problems that are otherwise computationally intractable. These algorithms mimic natural or evolutionary processes to efficiently search for solutions, making them a cornerstone of industrial optimization.