Affiliation:
1. The University of Nottingham
2. Shahrood University of Technology
3. The University of Sheffield
4. Eastern Mediterranean University
Abstract
Modified Augmented Lagrangian Genetic Algorithm (ALGA) and Quadratic Penalty Function Genetic Algorithm (QPGA) optimization methods are proposed to obtain truss structures with minimum structural weight using both continuous and discrete design variables. To achieve robust solutions, Compressed Sparse Row (CSR) with reordering of Cholesky factorization and Moore Penrose Pseudoinverse are used in case of non-singular and singular stiffness matrix, respectively. The efficiency of the proposed nonlinear optimization methods is demonstrated on several practical examples. The results obtained from the Pratt truss bridge show that the optimum design solution using discrete parameters is 21% lighter than the traditional design with uniform cross sections. Similarly, the results obtained from the 57-bar planar tower truss indicate that the proposed design method using continuous and discrete design parameters can be up to 29% and 9% lighter than traditional design solutions, respectively. Through sensitivity analysis, it is shown that the proposed methodology is robust and leads to significant improvements in convergence rates, which should prove useful in large-scale applications.
Publisher
Vilnius Gediminas Technical University
Subject
Strategy and Management,Civil and Structural Engineering
Reference18 articles.
1. Weight minimization of trusses with genetic algorithm
2. Haftka, R. T.; Gurdal, Z. 1982. Elements of structural optimization. Boston, Massachusetts: Kluwer Academic Publisher. 481 p.
Cited by
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