CMSRAS: A Novel Chaotic Multi-Specular Reflection Optimization Algorithm Considering Shared Nodes

Specular reflection algorithm (SRA) was a single population meta-heuristic inspired by the physical function of mirror. However, similar to most algorithms, it had disadvantages weak diversity, stagnation in local optimal and low convergence rate. In order overcome these shortcomings, chaotic multi-specular optimization considering shared nodes (CMSRAS) proposed combination strategy with node, improved Tent chaos Gaussian mutation strategy. Initially, SRA extended multi-population node initialized sequence improve quality initial solution enhance global search ability. Meanwhile, strengthen ability accuracy, disturbance were introduced into SRA. And then influence law sensitivity analysis CMSRAS between setting parameters obtained based on response surface method Sobol's method. Finally, compared both 12 state-of-the-art algorithms 8 well-known advanced performance evaluated comprehensive set 32 benchmark problems. addition, applied solve complex problems engineering structure. The results demonstrated that outperformed competitive efficiently real-life