Uncertainty-Aware Robust Optimization of Overhead Crane Girders Using MOIFWA with Fatigue Life Constraints

Bridge cranes are essential material-handling equipment, and their main girders must simultaneously satisfy the requirements of lightweight design, stiffness, strength, and fatigue life. Existing optimization studies on crane main girders are mostly based on deterministic methods, whereas the influences of uncertain factors such as plate thickness, material properties, load spectra, and fatigue parameters are rarely quantitatively analyzed. This paper proposes an uncertainty-oriented robust optimization framework for the design of bridge crane main girders. Robustness is rigorously defined as the insensitivity of structural performance to uncertain parameters and is quantified through probabilistic constraints and performance variance indices. A robustness index system comprising static stiffness, dynamic stiffness, static strength, dynamic strength, and fatigue life is established. An improved multi-objective fireworks algorithm (MOIFWA) is adopted, which integrates the explosion search mechanism of the fireworks algorithm with the fast non-dominated sorting and crowding distance strategy of NSGA-II. The cross-sectional dimensions of the main girder are taken as design variables; both mass and deflection are minimized while satisfying constraints on strength, stiffness, stability, and fatigue life. The feasibility of the optimized design is verified through finite element simulations using ANSYS 2022R1, ABAQUS 2025, and FE-Safe 2025. For a 32 t–25.5 m double-girder bridge crane, the optimized main girder achieves a 10.29% reduction in mass and a 5.35% reduction in deflection, with predicted fatigue lives of 34.68 years by the nominal stress/fracture mechanics method and 32.94 years by the ABAQUS/FE-Safe method. This framework provides a practical approach for designing crane girders that are lightweight and possess reliable fatigue performance under uncertainty.