Open AccessMember Sizing Optimization of Large Scale Steel Space Trusses Using a Symbiotic Organisms Search Algorithm
Author(s) -
Foek Tjong Wong,
Doddy Prayogo,
Reinard Eka Putra,
J Alwin Joseph
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1625/1/012019
Subject(s) - truss , metaheuristic , sizing , finite element method , particle swarm optimization , mathematical optimization , convergence (economics) , computer science , engineering , structural engineering , algorithm , mathematics , art , economics , visual arts , economic growth
A systematic approach of optimization is needed to achieve an optimal design of large and complex truss structures. In the last three decades, several researchers have developed and applied various metaheuristic optimization methods to the design of truss structures. This paper investigates a new metaheuristic algorithm called symbiotic organisms search (SOS) for member sizing optimization of relatively large steel trusses. The case studies include a 120-bar dome truss and a 942-bar tower truss. The structural analyses are carried out using the standard finite element method. The profiles of the truss members are circular hollow structural sections selected from a set of the American Institute of Steel Construction standard profiles. The design results using the SOS are then compared to those obtained using other metaheuristic methods, namely the particle swarm optimization, differential evolution, and teaching-learning-based optimization. The comparison shows the superior performance of the SOS in terms of the optimal solution, consistency, and convergence. Thus, the SOS is a good alternative for optimizing the design of steel truss structures in real engineering practice.