Topology optimization of nonlinear compliant mechanisms using the Artificial Bee Colony Algorithm

Abstract

Optimization techniques inspired by swarm intelligence have become increasingly popular during the last decade. They are characterized by a decentralized way of working that mimics the behavior of swarms with social insects, flock of birds, or schools of fish. The advantages of these approaches unlike the traditional techniques are their robustness and flexibility. Artificial Bee Colony Algorithm (ABCA) is one of the recently developed optimization algorithms, motivated by the intelligent behavior of honey bees. From the simulation studies carried out by Karaboga, ABCA was applied for finding the global minimum of benchmark function. As a result of that experiment, when compared to the existing other swarm based algorithm such as genetic algorithm (GA), particle swarm intelligence optimization (PSO), particle swarm inspired evolutionary algorithm (PS-EA), ABCA is very simple and very flexible. In this research, the artificial bee colony algorithm (ABCA) as one of swarm intelligence methods and finite element analysis are adopted for structural topology optimization. Since the ABCA was originally developed for continuous function optimization problems, this thesis describes considerable modifications made to the ABCA in order to solve discrete topology optimization problems. The structural topology optimization using ABCA is applied in various fields of static, dynamic and compliant mechanism (e.g. force and thermal) included in geometrical nonlinear and three dimensional problem. The following conclusions are obtained through the results of examples based on the ABCA; (1) The ABCA, using some modified and suggested methods, is very applicable and effective in topology optimization for obtaining a stable and robust optimal layout. (2) The optimal topology from the ABCA is nearly obtained in a half stage of the convergence iteration, since the volume constraint is applied from the beginning. (3) While the ABCA is applied to the topology optimization (e.g. static, dynamic and compliant mechanism design), various issues were occurred. This paper is considered to each of the issues and those solutions.