PERFORMANCE-BASED MULTI-OBJECTIVE OPTIMUM DESIGN FOR STEEL STRUCTURES WITH INTELLIGENCE ALGORITHMS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

LIANG J.C.; LI L.J.; HE J.N.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: International Journal of Optimization in Civil Engineering Year:2015 | Volume:5 | Issue:1 Page(s): 79-101

Download Full-Text

View:

353

Download:

169

Cites:

Information Journal Paper

Title

PERFORMANCE-BASED MULTI-OBJECTIVE OPTIMUM DESIGN FOR STEEL STRUCTURES WITH INTELLIGENCE ALGORITHMS

Author(s)

LIANG J.C. | LI L.J. | HE J.N. | Issue Writer Certificate

Keywords

PERFORMANCE-BASED SEISMIC DESIGN

STRUCTURAL OPTIMIZATION

HEURISTIC PARTICLE SWARM OPTIMIZER

MULTI-OBJECTIVE OPTIMISATION

Abstract

A multi-objective heuristic particle swarm optimiser (MOHPSO) based on Pareto multiobjective theory is proposed to solve multi-objective optimality problems. The optimality objectives are the roof displacement and structure weight. Two types of structure are analysed in this paper, a truss structure and a framework structure. Performance-based seismic analysis, such as classical and modal pushover analysis, is carried out for the structures. Four optimality algorithms, namely, NSGA-II, MOPSO, MGSO, and MOHPSO, were used for structural optimisation to compare the effectiveness of the algorithms. The calculation results indicate that MOHPSO outperformed the other algorithms in terms of solution stability, universality, and consistency of the distribution of the Pareto front and the ability to consider constraints. The population can converge to the true Pareto front in the latter generations, which indicates that MOHPSO is effective for engineering multiobjective optimality problems.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

LIANG, J.C., LI, L.J., & HE, J.N.. (2015). PERFORMANCE-BASED MULTI-OBJECTIVE OPTIMUM DESIGN FOR STEEL STRUCTURES WITH INTELLIGENCE ALGORITHMS. INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING, 5(1), 79-101. SID. https://sid.ir/paper/329405/en

Vancouver: Copy

LIANG J.C., LI L.J., HE J.N.. PERFORMANCE-BASED MULTI-OBJECTIVE OPTIMUM DESIGN FOR STEEL STRUCTURES WITH INTELLIGENCE ALGORITHMS. INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING[Internet]. 2015;5(1):79-101. Available from: https://sid.ir/paper/329405/en

IEEE: Copy

J.C. LIANG, L.J. LI, and J.N. HE, “PERFORMANCE-BASED MULTI-OBJECTIVE OPTIMUM DESIGN FOR STEEL STRUCTURES WITH INTELLIGENCE ALGORITHMS,” INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING, vol. 5, no. 1, pp. 79–101, 2015, [Online]. Available: https://sid.ir/paper/329405/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops