Multiobjective Simultaneous Topology, Shape and Sizing Optimization of Trusses Using Evolutionary Optimizers

International Conference on Aerospace and Mechanical Engineering 2017

航空航天工程;机械制造

Techasen, Teerapol^1 ; Wansasueb, Kittinan^1 ; Panagant, Natee^1 ; Pholdee, Nantiwat^1 ; Bureerat, Sujin^1

Sustainable and Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen

40002, Thailand^1

关键词: Differential Evolution;    Evolutionary optimizers;    Hypervolume indicators;    Multi-objective functions;    Multiobjective evolutionary algorithms;    Optimization problems;    Population based incremental learning;    Structural topologies;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/370/1/012029/pdf
DOI  :  10.1088/1757-899X/370/1/012029

学科分类：航空航天科学

来源: IOP

【 摘 要 】

This paper presents design of two-dimensional (2D) trusses to achieve their simultaneously optimal topology, shape and size. The optimization problems are posed to search for structural topology, shape and sizing such that multiobjective functions consisting of mass and compliance are minimized while stresses and displacements are assigned as design constraints. The design approach is based on a ground structure approach meaning that a structure having all possible truss element connection is initiated. Design variables determine how to remove or maintain those elements and at the same time nodal positions are varied. Truss optimization problems are assigned whereas a number of multiobjective evolutionary algorithms (MOEAs) are implemented to solve the problems. Based on the hypervolume indicator, it is found that Hybridization of Real-Code Population-Based Incremental Learning and Differential Evolution (RPBIL-DE) is the best performer. This study gives the baseline results for implementing MOEAs for simultaneous topology, shape and sizing optimization of trusses.