AN ARTIFICIAL INTELLIGENCE MODEL BASED ON LS-SVM FOR THIRD-PARTY LOGISTICS PROVIDER SELECTION

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.

VAHDANI B.; SADIGH BEHZADI SH.; MOUSAVI S.M.

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

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS Year:2015 | Volume:7 | Issue:4 Page(s): 301-311

Download Full-Text

Persian Verion

View:

932

Download:

359

Cites:

Information Journal Paper

Title

AN ARTIFICIAL INTELLIGENCE MODEL BASED ON LS-SVM FOR THIRD-PARTY LOGISTICS PROVIDER SELECTION

Author(s)

VAHDANI B. | SADIGH BEHZADI SH. | MOUSAVI S.M. | Issue Writer Certificate

Keywords

ARTIFICIAL INTELLIGENCE (AI)Q2

LEAST SQUARES SUPPORT VECTOR MACHINE (LS-SVM)Q2

CROSS VALIDATIONQ2

THIRD-PARTY LOGISTICS (3PL) PROVIDER SELECTION PROBLEMQ2

Abstract

The use of third-party logistics (3PL) providers is regarded as new strategy in logistics management. The relationships by considering 3PL are sometimes more complicated than any classical logistics supplier relationships. These relationships have taken into account as a well-known way to highlight organizations' flexibilities to regard rapidly uncertain market conditions, follow core competencies, and provide long-term growth strategies. Choosing service providers has been considered as a notable research area in the last two decades. The review of the literature represents that neural networks have proposed better performance than traditional methods in this area. Therefore, in this paper, a new enhanced artificial intelligence (AI) approach is taken into consideration to assist the decision making for the logistics management which can be successfully presented in cosmetics industry for long-term prediction of the real performance data. The presented AI approach is based on modern hybrid neural networks to improve the decision making for the 3PL selection. The model can predict the overall performance of the 3PL according to least squares support vector machine and CROSS VALIDATION technique. In addition, the proposed AI approach is given for the 3PL selection in a real case study for the cosmetics industry. The computational results indicate that the proposed AI approach provides high performance and accuracy through the real-life situations prediction along with comparing two other two well-known AI methods.

Cites

No record.

References

Cite

APA: Copy

VAHDANI, B., SADIGH BEHZADI, SH., & MOUSAVI, S.M.. (2015). AN ARTIFICIAL INTELLIGENCE MODEL BASED ON LS-SVM FOR THIRD-PARTY LOGISTICS PROVIDER SELECTION. INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS, 7(4), 301-311. SID. https://sid.ir/paper/231700/en

Vancouver: Copy

VAHDANI B., SADIGH BEHZADI SH., MOUSAVI S.M.. AN ARTIFICIAL INTELLIGENCE MODEL BASED ON LS-SVM FOR THIRD-PARTY LOGISTICS PROVIDER SELECTION. INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS[Internet]. 2015;7(4):301-311. Available from: https://sid.ir/paper/231700/en

IEEE: Copy

B. VAHDANI, SH. SADIGH BEHZADI, and S.M. MOUSAVI, “AN ARTIFICIAL INTELLIGENCE MODEL BASED ON LS-SVM FOR THIRD-PARTY LOGISTICS PROVIDER SELECTION,” INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS, vol. 7, no. 4, pp. 301–311, 2015, [Online]. Available: https://sid.ir/paper/231700/en

Related Journal Papers