Damage Detection of Steel Roof Systems Using Planet Optimization Algorithm

In this work, an inverse method for damage detection studies is developed based on Planet Optimization Algorithm (POA). To demonstrate effectiveness the POA, numerical investigations are implemented on the bivariate Michalewicz function, and 15 functions from the CEC2014 benchmark in a 30-dimensional space (including a comparison between POA and several well-known candidates). The achieved results illustrate that in terms of stability, robustness, and quality of the obtained solution, POA is one of most outstanding optimization algorithms. POA ranks No. 1 in functions F1, F4, F7, F8, F13, while POA is highly ranked and sufficiently competitive with the other contenders in the rest of tests. Based on these considerations, for the first time, an application for multi-damage detection of steel roof truss systems using POA is presented herein. Through comparison with other famous algorithms, POA has outperformed computational cost with fast convergence speed. POA has only, respectively, 99.5%, 98.6%, and 97.2% time-consuming for computational cost when compared with GWO, AOA, and PSO. Also, the results proved that this technique provides an efficient solution to the complex problem with many constraints in unknown search space.