Surveying the performance of four meta-heuristic optimization algorithm in weight optimization of truss structures

Optimization is considered as an art to discover the best solution among the available ones. Meta-heuristic algorithms are one type of the random algorithms used for finding the optimized solutions. Since the simplicity of the concepts and the acceptable performance in a wide range of issues, this group of algorithms has lately been the center of concentrations. The present study investigates and compares the meta-heuristic optimization algorithms such as artificial bee colony (ABC), gravitational search algorithm (GSA), genetics (GA), and firefly algorithms (FA) for truss structures with a focus on its weight optimization.