TY - JOUR
T1 - Shape optimization of thin-walled steel sections using graph theory and ACO algorithm
AU - Sharafi, P.
AU - Teh, Lip H.
AU - Hadi, Muhammad N. S.
PY - 2014
Y1 - 2014
N2 - This paper presents an intuitive procedure for the shape and sizing optimizations of open and closed thin-walled steel sections using the graph theory. The goal is to find shapes of optimum mass and strength (bi-objectives). The shape optimization of open sections is treated as a multi-objective all-pairs shortest path problem, while that of closed sections is treated as a multi-objective minimum mean cycle problem. The sizing optimization of a predetermined shape is treated as a multi-objective single-pair shortest path problem. Multi-colony ant algorithms are formulated for solving the optimization problems. The verification and numerical examples involving the shape optimizations of open and closed thin-walled steel sections and the sizing optimization of trapezoidal roof sheeting are presented.
AB - This paper presents an intuitive procedure for the shape and sizing optimizations of open and closed thin-walled steel sections using the graph theory. The goal is to find shapes of optimum mass and strength (bi-objectives). The shape optimization of open sections is treated as a multi-objective all-pairs shortest path problem, while that of closed sections is treated as a multi-objective minimum mean cycle problem. The sizing optimization of a predetermined shape is treated as a multi-objective single-pair shortest path problem. Multi-colony ant algorithms are formulated for solving the optimization problems. The verification and numerical examples involving the shape optimizations of open and closed thin-walled steel sections and the sizing optimization of trapezoidal roof sheeting are presented.
UR - http://handle.uws.edu.au:8081/1959.7/549046
U2 - 10.1016/j.jcsr.2014.05.026
DO - 10.1016/j.jcsr.2014.05.026
M3 - Article
SN - 0143-974X
VL - 101
SP - 331
EP - 341
JO - Journal of Constructional Steel Research
JF - Journal of Constructional Steel Research
ER -