Ship Engineer Inspired Optimization Algorithm

This paper proposes a new heuristic optimization algorithm inspired by the thinking of naval engineers—the Ship Engineer Inspired Optimization (SEIO). This algorithm emulates the mindset of naval engineers during ship design and commissioning, employing principles such as resistance-stability trade-offs, local fine-tuning, global feedback, system coupling, and risk control. It establishes a comprehensive mathematical optimization model and iterative mechanism. SEIO utilizes dynamic fitness weights, local gradient adjustment, neighbor learning, and risk-controlled step sizes to achieve efficient search for multi-objective optimization problems. This paper systematically expounds on the algorithmic design concept, mathematical formulas, and core mechanisms of SEIO, providing a new methodological tool for the field of engineering optimization.