Comparison of gradient and nongradient algorithms in the structural optimization course

Abstract

Gradient and nongradient optimization algorithms are currently available for structural design in structural optimization course. Despite the successful application of gradient algorithm in structural optimization, nongradient algorithm is also extensively adopted to solve the structural optimization problem. However, the efficiency of nongradient algorithm has caused a heated debate recently. To clarify this issue for the graduate students, sequential linear programming and genetic algorithm are, respectively, chosen as the representatives of gradient and nongradient algorithms to solve truss size optimization problem. Firstly, the size optimization formulations of truss structure for sequential linear programming and genetic algorithm are summarized, respectively. Secondly, an educational finite element software for truss structure is developed by using the object-oriented programming to create the software framework. This study aims to provide an open-source, extensible, and benchmarking software, which do assist the students to understand the structural optimization process in engineering education. Finally, two benchmarking examples are introduced to compare the efficiency and accuracy of sequential linear programming and genetic algorithm.

Shaping of Curvilinear Steel Bar Structures for Variable Environmental Conditions Using Genetic Algorithms—Moving towards Sustainability

“…Initially, Grasshopper was mostly applied for parametric modeling in architecture and fabrication problems. However, thanks to its capabilities and thanks to enriching it with new plug-ins, it has begun to be applied in structural engineering [ 1 , 42 , 46 , 47 ]. The Grasshopper parametric scripts created for the presented research defined variable shapes, dimensions and topologies of the structures being shaped, in order to explore their forms.…”

“…Algorithmic-aided structural optimization can be performed using both gradient and non-gradient algorithms. An explanation of this issue is presented with an example of the truss size optimization problem in reference [ 42 ]. Open-source and benchmarking software for helping one to understand the process of structural optimization is provided there.…”

An effective teaching strategy for engineering mechanics to develop structural optimization modeling skills of undergraduates

“…28 Some important issues, such as sensitivity analysis and iterative algorithms, are briefly introduced for supporting students to select the appropriate solver and set the solver parameters. Related works 20,21 and papers 30,31 are recommended for post-course study to further understand these issues. Finally, through comparing the design results from the traditional method and optimization modeling, it can be seen that the latter is featured with a smaller cross-sectional area when just satisfying the design requirements.…”