Optimal design of spatial structures by a novel meta-heuristic algorithm: Sound energy optimizer

Sound signals are used by various species of living creaters to commonicate with each other. Scientific experiments have demonstrated that sound energy can travel through media and cause the receiver objects to vibrate or move. The present work simulates such a phenomenon in development of a new meta-heuristic algorithm called: Sound Energy Optimizer (SEO). Concerning physical rules, SEO leverages natural or ambient sounds for optimization. SEO utilizes a tunable virtual machine to control the decaying pattern of the sound energy in a medium representing the search space. Performance of the proposed algorithm is first evaluated on unconstrained optimization of some mathematical test functions. Then, a variety of pin-jointed structural problems are optimized including space tower, double-layer grid, barrel vault, helipad structure and power transmission towers. In this set, performance evaluation is done not only against the previous works but also by running SEO versus eight recent meta-heuristics under fair comparison conditions. New quantitative indices are introduced and traced as well as the common statistical measures and convergence curves. The results demonstrate competitive performance of SEO versus recent meta-heuristics in the discrete and continuous design of spatial structures.