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A comparative study of several bio-inspired algorithms in cost optimization of cellular beams
Author(s) -
A Tjahjono,
Elfrida Wijayanti,
Doddy Prayogo,
Wong Foek Tjong
Publication year - 2021
Publication title -
iop conference series earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/907/1/012001
Subject(s) - particle swarm optimization , metaheuristic , beam (structure) , consistency (knowledge bases) , differential evolution , mathematical optimization , focus (optics) , convergence (economics) , selection (genetic algorithm) , computer science , multi swarm optimization , point (geometry) , algorithm , mathematics , structural engineering , engineering , artificial intelligence , optics , physics , geometry , economics , economic growth
Castellated beams are commonly used in steel construction. This study will focus on castellated beams with circular-shaped openings, which are known as cellular beams. Cost optimization of cellular beams is needed to maintain cost efficiency. The optimization considers the selection of a root beam, the diameter of holes, and the total number of holes in the beam as the variables. Four metaheuristic algorithms are used to optimize the design, namely, the particle swarm optimization (PSO), differential evolution (DE), symbiotic organisms search (SOS), and artificial bee colony (ABC). A four-meter span beam with a 50 kN point live load in the middle of the beam and a 5 kN/m uniformly-distributed dead load are taken as the case study. The results indicate that the SOS algorithm yields the best optimization results in terms of the average, consistency, and convergence behavior with a 30 out of 30 success rates.

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