A modified ant colony optimization algorithm for dynamic topology optimization

• MACO is a robust and stable algorithm in dynamic topology optimization problems.
• MACO is more effective and suitable comparing with the standard ACO.
• Convergence rate of MACO is competitive with that of BESO.
• Optimal natural frequencies from MACO are slightly higher than those from BESO.

A modified ant colony optimization (MACO) algorithm implementing a new definition of pheromone and a new cooperation mechanism between ants is presented in this paper. The sensitivity of structural response to the presence of each element included in the finite element (FE) model is evaluated. The study aims to improve the suitability and computational efficiency of the ant colony optimization algorithm in dynamic topology optimization problems. The natural frequencies of the structure must be maximized yet satisfying a constraint on the final volume. Optimization results obtained in three test cases indicate that MACO is more efficient and robust than standard ACO in solving dynamic topology optimization problems.