English Abstract
Abstract :
The aim of optimization is to achieve the most favorable design considering a
prioritized set of criteria or constraints. In the realm of engineering advancements, it is
crucial for engineers to explore beyond conventional methods. While traditional
approaches may provide comfort and familiarity, designers must recognize the
increasing significance of optimization methods. These methods play a crucial role in
saving both time and money while simultaneously reducing errors. This research
represents a modest stride toward comprehending the advantages that optimization
can bring to structural design. It aims to contribute to one of the primary goals of
every engineer: designing structures that are not only safe but also economically and
environmentally sustainable.
To accomplish this, design optimization algorithms such as ABC (The Artificial Bee
Colony), TLBO (Teaching Learning Based Optimization), and DE (Differential
Evolution) were employed to determine the optimal cross-sectional dimensions of
columns following the AISC-LRFD design provisions. The software tool ETABS was
utilized to obtain the frame's response to external loads, and the optimization
iterations were executed using MATLAB. Altering the cross-sectional properties of
the members in the 3-D steel frame leads to changes in their performance under
external loads, necessitating a new analysis. This is facilitated through the use of the
Application Programming Interface (API) feature of ETABS, establishing a link
between the coded MATLAB program and ETABS for bidirectional data exchange.
Iterations continue until the convergence criteria are satisfied.
It was found that the utilized optimum design algorithms were able to optimize the
weights and reduce them to the minimum possible sections. It was also found that the
proposed TLBO and DE are efficient and better than the standard ABC in terms of the
convergence history and providing the best results.
