Swarm Intelligence Topology Optimization Based on Artificial Bee Colony Algorithm

Abstract

Artificial bee colony algorithm (ABCA) as one of swarm intelligence methods and finite element analysis are first adopted for structural topology optimization. The objective of this paper is to suggest how to apply ABCA and examine the effectiveness and applicability of the suggested ABCA in structural topology optimization. Since ABCA was originally developed for continuous function optimization problems, this paper describes considerable modifications made to ABCA in order to obtain an optimal topology for a structure. The waggle index update rule and fitness update scheme are developed and applied for obtaining stable and robust optimal topology and accelerating convergence rate based on the suggested ABCA. Typical examples of 2D structural models and a 3D structural problem are provided for comparing to the solid isotropic microstructure with penalization (SIMP). The desirable conclusions are obtained through the results of the examples based on the suggested ABCA.