Engineering Problem

Engineering problem-solving is currently undergoing a transformation driven by advancements in optimization algorithms and machine learning. Research focuses on developing and refining metaheuristic algorithms (like modified Fitness Dependent Optimizers and Sea Horse Optimizers) to efficiently explore complex design spaces and find optimal solutions for various engineering challenges, including those with constraints. These methods are being compared against and sometimes integrated with established techniques like the finite element method and are increasingly applied to real-world problems across diverse fields. The ultimate goal is to improve the efficiency and effectiveness of engineering design processes, leading to better, more cost-effective solutions.