OPTIMIZATION OF BLASTING COST IN LIMESTONE MINES BY PSO METAHEURISTIC ALGORITHM

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.

Bastami Reza; Aghajani bazzazi Abbas; Hamidian Shoormasti Hadi; Ahangari Kaveh

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

Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF MINING ENGINEERING (IRJME) Year:2019 | Volume:14 | Issue:44 Page(s): 87-99

Download Full-Text

Persian Verion

View:

957

Download:

Cites:

Information Journal Paper

Title

OPTIMIZATION OF BLASTING COST IN LIMESTONE MINES BY PSO METAHEURISTIC ALGORITHM

Author(s)

Bastami Reza | Aghajani bazzazi Abbas | Hamidian Shoormasti Hadi | Ahangari Kaveh | Issue Writer Certificate

Keywords

Blasting costQ1

Limestone minesQ1

nonlinear multivariate regressionQ1

Particles swarm Optimization algorithmQ1

OptimizationQ2

Abstract

In this research, a model is presented to predict the Blasting cost by collecting blasting data from six Limestone mines in Iran using a nonlinear multivariate regression. This model has a higher correlation coefficient (0. 913) and lower root mean square error (1089) than the linear multivariate regression model, thus indicated a better compliance with the actual Blasting costs. In this study, in addition to achieving the Blasting cost function using a nonlinear multivariate regression method, a model was proposed for blasting limiting functions including fragmentation, fly rock, and back break. These functions were used as constraints to the particle swarm Optimization (PSO) metaheuristic algorithm in order to optimize the Blasting cost. Results showed that the spacing, borehole number, and length of holes were 3. 6 m, 462 loops, and 13 m as blasting design parameters, respectively. The mean grading, fly rock, and back break 44 cm, 84. 5 m and 3. 6 m, respectively, were the blasting constraints, and also the Blasting cost was calculated to be 6235 Rials per ton. These results showed a 12. 9% reduction in Blasting costs, and an optimal control of the adverse consequences of blasting in comparison to the conventional blasting patterns. Keywords: Blasting cost, Limestone mines, nonlinear multivariate regression, particle swarm Optimization algorithm.

Cites

No record.

References

No record.

Cite

APA: Copy

Bastami, Reza, Aghajani bazzazi, Abbas, Hamidian Shoormasti, Hadi, & Ahangari, Kaveh. (2019). OPTIMIZATION OF BLASTING COST IN LIMESTONE MINES BY PSO METAHEURISTIC ALGORITHM. IRANIAN JOURNAL OF MINING ENGINEERING (IRJME), 14(44 ), 87-99. SID. https://sid.ir/paper/117146/en

Vancouver: Copy

Bastami Reza, Aghajani bazzazi Abbas, Hamidian Shoormasti Hadi, Ahangari Kaveh. OPTIMIZATION OF BLASTING COST IN LIMESTONE MINES BY PSO METAHEURISTIC ALGORITHM. IRANIAN JOURNAL OF MINING ENGINEERING (IRJME)[Internet]. 2019;14(44 ):87-99. Available from: https://sid.ir/paper/117146/en

IEEE: Copy

Reza Bastami, Abbas Aghajani bazzazi, Hadi Hamidian Shoormasti, and Kaveh Ahangari, “OPTIMIZATION OF BLASTING COST IN LIMESTONE MINES BY PSO METAHEURISTIC ALGORITHM,” IRANIAN JOURNAL OF MINING ENGINEERING (IRJME), vol. 14, no. 44 , pp. 87–99, 2019, [Online]. Available: https://sid.ir/paper/117146/en

Related Journal Papers