Journal of Bionic Engineering ›› 2021, Vol. 18 ›› Issue (3): 721-732.doi: 10.1007/s42235-021-0041-z

• • 上一篇    

An Improved Whale Algorithm and Its Application in Truss Optimization

Fengguo Jiang1, Lutong Wang1, Lili Bai2*   

  1. 1. School of Architecture and Civil Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China
    2. College of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150001, China
  • 收稿日期:2020-11-06 修回日期:2021-03-16 接受日期:2021-04-14 出版日期:2021-05-10 发布日期:2021-11-30
  • 通讯作者: Lili Bai E-mail:lily0907@hrbeu.edu.cn
  • 作者简介:Fengguo Jiang1, Lutong Wang1, Lili Bai2*

An Improved Whale Algorithm and Its Application in Truss Optimization

Fengguo Jiang1, Lutong Wang1, Lili Bai2*   

  1. 1. School of Architecture and Civil Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China
    2. College of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150001, China
  • Received:2020-11-06 Revised:2021-03-16 Accepted:2021-04-14 Online:2021-05-10 Published:2021-11-30
  • Contact: Lili Bai E-mail:lily0907@hrbeu.edu.cn
  • About author:Fengguo Jiang1, Lutong Wang1, Lili Bai2*

摘要: 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.


关键词: improve whale optimization algorithm, differential evolutionary algorithm, cloud theory, simulating optimization, bionic algorithm

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