Topology and Size Optimization of Trusses with Static and Dynamic Bounds by Modified Symbiotic Organisms Search

Abstract

In this study, a modified version of the symbiotic organisms search (SOS) is proposed for topology and sizing of two-dimensional (2D) and three-dimensional (3D) trusses with static and dynamic criteria. Symbiotic organisms search simulates the symbiotic attachment among different species, such as mutualism, commensalism, and parasitism, to stay alive in the environment. The heuristic nature of the mutualism phase allows the search to jump into nonvisited regions (exploration) and also permits a local search of visited regions (exploitation). As the optimization process progresses, a good balance between an exploration and exploitation has a stronger influence on the generated population. Thus, adaptive control of the benefit factor is now incorporated in the mutualism phase to propose a modified SOS (MSOS) algorithm. Symbiotic organisms search and MSOS are tested on trusses assumed with multiple loading conditions and subjected to natural frequency, stress, displacement, buckling, and kinematic stability constraints. Such a design problem turns out to be more challenging if the topology and size variables are considered with the static and dynamic bounds. Symbiotic organisms search and MSOS are compared with the previous studies. The results show that MSOS is the better performer compared to SOS and other state-of-the-art algorithms.