TOA: A Novel Metaheuristic Optimization Algorithm Inspired by Marine Turtle Navigation

This study proposes the Turtle Optimization Algorithm (TOA), a bio-inspired metaheuristic motivated by the long-distance navigation behavior of marine turtles. TOA integrates four main mechanisms: geomagnetic orientation modeled through sinusoidal modulation, ocean current drift, stamina-aware adaptive reference selection, and an Environmental Coordination Strategy (ECS). These mechanisms are jointly designed to balance exploration and exploitation while reducing premature convergence. The TOA was evaluated on 29 benchmark functions, including classical and CEC2019 benchmarks, and compared with established and recent metaheuristic algorithms. Friedman analysis revealed statistically significant differences among the compared methods (p < 0.05). The TOA achieved first place average ranks of 1.43 and 1.33 in two classical benchmark comparison groups. On CEC2019, TOA obtained average ranks of 1.60, 3.20, and 2.70, corresponding to first, second, and first place, respectively. The practical applicability of the TOA was further evaluated on three constrained engineering design problems––welded beam, speed reducer, and clutch brake design––where competitive solutions were obtained. Overall, the results demonstrate that the TOA provides a competitive and robust optimization framework across diverse benchmark and engineering problems.