FINDING THE SHORTEST HAMILTONIAN PATH FOR IRANIAN CITIES USING HYBRID SIMULATED ANNEALING AND ANT COLONY OPTIMIZATION 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.

YAGHINI M.; MOMENI M.; SARMADI M.

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

Journal Paper

Paper Information

Journal: International Journal of Industrial Engineering & Production Research Year:2011 | Volume:22 | Issue:1 Page(s): 31-42

Download Full-Text

View:

343

Download:

184

Cites:

Information Journal Paper

Title

FINDING THE SHORTEST HAMILTONIAN PATH FOR IRANIAN CITIES USING HYBRID SIMULATED ANNEALING AND ANT COLONY OPTIMIZATION ALGORITHMS

Author(s)

YAGHINI M. | MOMENI M. | SARMADI M. | Issue Writer Certificate

Keywords

IRANIAN CITIES

TRAVELING SALESMAN PROBLEM

HAMILTONIAN PATH

SIMULATED ANNEALING ALGORITHM

ANT COLONYOPTIMIZATION ALGORITHM

Abstract

The TRAVELING SALESMAN PROBLEM is a well-known and important combinatorial optimization problem. The goal of this problem is to find the shortest HAMILTONIAN PATH that visits each city in a given list exactly once and then returns to the starting city. In this paper, for the first time, the shortest HAMILTONIAN PATH is achieved for 1071 IRANIAN CITIES. For solving this large-scale problem, two hybrid efficient and effective metaheuristic algorithms are developed. The simulated annealing and ant colony optimization algorithms are combined with the local search methods. To evaluate the proposed algorithms, the standard problems with different sizes are used. The algorithms parameters are tuned by design of experiments approach and the most appropriate values for the parameters are adjusted. The performance of the proposed algorithms is analyzed by quality of solution and CPU time measures. The results show high efficiency and effectiveness of the proposed algorithms.

Cites

No record.

References

No record.

Cite

APA: Copy

YAGHINI, M., MOMENI, M., & SARMADI, M.. (2011). FINDING THE SHORTEST HAMILTONIAN PATH FOR IRANIAN CITIES USING HYBRID SIMULATED ANNEALING AND ANT COLONY OPTIMIZATION ALGORITHMS. INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION RESEARCH (IJIE) (ENGLISH), 22(1), 31-42. SID. https://sid.ir/paper/585375/en

Vancouver: Copy

YAGHINI M., MOMENI M., SARMADI M.. FINDING THE SHORTEST HAMILTONIAN PATH FOR IRANIAN CITIES USING HYBRID SIMULATED ANNEALING AND ANT COLONY OPTIMIZATION ALGORITHMS. INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION RESEARCH (IJIE) (ENGLISH)[Internet]. 2011;22(1):31-42. Available from: https://sid.ir/paper/585375/en

IEEE: Copy

M. YAGHINI, M. MOMENI, and M. SARMADI, “FINDING THE SHORTEST HAMILTONIAN PATH FOR IRANIAN CITIES USING HYBRID SIMULATED ANNEALING AND ANT COLONY OPTIMIZATION ALGORITHMS,” INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION RESEARCH (IJIE) (ENGLISH), vol. 22, no. 1, pp. 31–42, 2011, [Online]. Available: https://sid.ir/paper/585375/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops