HYBRID COLLIDING BODIES OPTIMIZATION AND SINE COSINE ALGORITHM FOR OPTIMUM DESIGN OF STRUCTURES

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.

Ilchi Ghazaan M.; Salmani Oshnari A.H.; Salmani Oshnari A.M.

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:2023 | Volume:13 | Issue:1 Page(s): 17-38

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

HYBRID COLLIDING BODIES OPTIMIZATION AND SINE COSINE ALGORITHM FOR OPTIMUM DESIGN OF STRUCTURES

Author(s)

Ilchi Ghazaan M. | Salmani Oshnari A.H. | Salmani Oshnari A.M. | Issue Writer Certificate

Keywords

Colliding Bodies Optimization

Sine Cosine Algorithm

Structural Design

Discrete and Continuous Optimization

Metaheuristic Algorithms.

Abstract

Colliding Bodies Optimization (CBO) is a population-based metaheuristic algorithm that complies physics laws of momentum and energy. Due to the stagnation susceptibility of CBO by premature convergence and falling into local optima, some meritorious methodologies based on Sine Cosine Algorithm and a mutation operator were considered to mitigate the shortcomings mentioned earlier. Sine Cosine Algorithm (SCA) is a stochastic optimization method that employs sine and cosine based mathematical models to update a randomly generated initial population. In this paper, we developed a new hybrid approach called hybrid CBO with SCA (HCBOSCA) to obtain reliable Structural Design optimization of discrete and continuous variable structures, where a memory was defined to intensify the convergence speed of the algorithm. Finally, three structural problems were studied and compared to some state of the art optimization methods. The experimental results confirmed the competence of the proposed algorithm.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans