MOSFOA: Multi-objective Starfish Optimization Algorithm

Multiobjective Starfish Optimization Algorithm for Engineering Design and Optimal Power Flow Problems

The Multi-Objective Starfish Optimization Algorithm (MOSFOA) is a robust bio-inspired optimization method developed to solve complex multi-objective engineering problems. As an extension of the Starfish Optimization Algorithm (SFOA), MOSFOA mimics starfish behaviors such as exploration, predation, and regeneration to achieve an effective balance between global exploration and local exploitation. The algorithm integrates elitist non-dominated sorting and crowding distance mechanisms to guide the population toward the Pareto-optimal front while preserving solution diversity. MOSFOA has been validated using standard benchmark functions (ZDT and DTLZ) and real-world applications, including engineering design and optimal power flow in power systems. Performance evaluation using IGD and Hypervolume metrics demonstrates that MOSFOA provides superior convergence, diversity, and stability compared to several state-of-the-art multi-objective optimization algorithms, making it a reliable and scalable tool for practical optimization applications.