Abstract: The current Whale Optimization Algorithm (WOA) has several drawbacks, such as slow convergence, low solution accuracy and easy to fall into the local optimal solution. To overcome these drawbacks, an improved Whale Optimization Algorithm (IWOA) is proposed in this study. IWOA can enhance the global search capability by two measures. First, the crossover and mutation operations in Differential Evolutionary algorithm (DE) are combined with the whale optimization algorithm. Second, the cloud adaptive inertia weight is introduced in the position update phase of WOA to divide the population into two subgroups, so as to balance the global search ability and local development ability. ANSYS and Matlab are used to establish the structure model. To demonstrate the application of the IWOA, truss structural optimizations on 52-bar plane truss and 25-bar space truss were performed, and the results were are compared with that obtained by other optimization algorithm. It is verified that, compared with WOA, the IWOA has higher efficiency, fast convergence speed, better solution accuracy and stability. So IWOA can be used in the optimization design of large truss structures.

Key words: improve whale optimization algorithm, differential evolutionary algorithm, cloud theory, simulating optimization, bionic algorithm