An Improved Pity Beetle Algorithm for Solving Constrained Engineering Design Problems

To cope with increasingly complex models of engineering design problems and to obtain more accurate design solutions, this paper proposed an improved population-based, bio-inspired optimization algorithm, called the pity beetle algorithm based on pheromone dispersion model (PBA-PDM). PBA-PDM enables a local and global search for optimization problems through the pheromone release mechanisms in female beetles and the interaction relationship between male beetles. The experimental results compared with other state-of-the-art metaheuristic optimization algorithms show that PBA-PDM has an ideal performance when dealing with both classical test functions and CEC2017 benchmark test functions. Then, the PBA-PDM is applied in dealing with real-world constrained engineering design problems to verify the effectiveness and applicability. The above experimental results show that the PBA-PDM proposed in this paper is an effective and efficient algorithm for solving real-world optimization problems.

Automated summary

This paper proposes an improved population-based, bio-inspired optimization algorithm based on the pheromone dispersion model, which is suitable for complex engineering design problems. The experimental results demonstrate that the algorithm performs well and efficiently in handling various test functions and real-world engineering design problems.