Discrete sizing optimization of steel trusses under multiple displacement constraints and load cases using guided stochastic search technique

• Published in: Structural and multidisciplinary optimization Vol. 52; no. 2; pp. 383 - 404
• Main Authors: Azad, S. Kazemzadeh, Hasançebi, O.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2015; Springer Nature B.V
• Subjects: Computational efficiency; Computational Mathematics and Numerical Analysis; Design optimization; Displacement; Engineering; Engineering Design; Industrial Application; Minimum weight; Optimization techniques; Search process; Sizing; Structural analysis; Theoretical and Applied Mechanics; Trusses; Integrated force method; Discrete sizing; AISC-LRFD specifications; Structural optimization; Steel trusses; Guided stochastic search
• ISSN: 1615-147X; 1615-1488
• DOI: 10.1007/s00158-015-1233-0

The guided stochastic search (GSS) is a computationally efficient design optimization technique, which is originally developed for discrete sizing optimization problems of steel trusses with a single displacement constraint under a single load case. The present study aims to investigate the GSS in a more general class of truss sizing optimization problems subject to multiple displacement constraints and load cases. To this end, enhancements of the GSS are proposed in the form of two alternative approaches that enable the technique to deal with multiple displacement/load cases. The first approach implements a methodology in which the most critical displacement direction is considered only when guiding the search process. The second approach, however, takes into account the cumulative effect of all the critical displacement directions in the course of optimization. Advantage of the integrated force method of structural analysis is also utilized for further reduction of the computational effort in these approaches. The proposed enhancements of GSS are investigated and compared with some selected techniques of design optimization through six truss structures that are sized for minimum weight. The numerical results reveal that both enhancements generally provide promising solutions with an insignificant computational effort.