A Reliability-based Design optimization of Crane Metallic Structure based on Ant colony optimization and LHS

Design optimization for crane metal structures (CMSs) is of great significance to reducing the weight and cost of structure. Although uncertainty is an inherent property existing in structure and deterministic design optimization (DDO) may result in an unreliable structure, optimization design considering uncertainty factors in crane structure is rare in studies at present. In view of this, the reliability-based design optimization (RBDO) is employed to the design of CMSs with random design variables and parameters in our research work. A discrete double loop RBDO model was constructed. In the inner loop, Latin hypercube sampling (LHS) combining with Monte Carlo simulation (MCS) were used to analyze the reliability of every design point of every constraint. In the outer loop, the ant colony optimization (ACO) algorithm was utilized to obtain the optimal result satisfying deterministic and probabilistic constraints. The engineering case shows that compared with the DDO, the RBDO can achieve a better tradeoff between cost and reliability based on security requirements.