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JCR Impact Factor: 0.800
JCR 5-Year IF: 1.000
SCOPUS CiteScore: 2.0
Issues per year: 4
Current issue: Feb 2024
Next issue: May 2024
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PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

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  4/2010 - 13

 HIGH-IMPACT PAPER 

Genetic Algorithm-based Dynamic Vehicle Route Search using Car-to-Car Communication

OH, B. See more information about OH, B. on SCOPUS See more information about OH, B. on IEEExplore See more information about OH, B. on Web of Science, NA, Y. See more information about  NA, Y. on SCOPUS See more information about  NA, Y. on SCOPUS See more information about NA, Y. on Web of Science, YANG, J. See more information about  YANG, J. on SCOPUS See more information about  YANG, J. on SCOPUS See more information about YANG, J. on Web of Science, PARK, S. See more information about  PARK, S. on SCOPUS See more information about  PARK, S. on SCOPUS See more information about PARK, S. on Web of Science, NANG, J. See more information about  NANG, J. on SCOPUS See more information about  NANG, J. on SCOPUS See more information about NANG, J. on Web of Science, KIM, J. See more information about KIM, J. on SCOPUS See more information about KIM, J. on SCOPUS See more information about KIM, J. on Web of Science
 
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Download PDF pdficon (4,747 KB) | Citation | Downloads: 1,763 | Views: 4,780

Author keywords
adaptive system, genetic algorithm, traffic information system

References keywords
genetic(10), algorithm(6), routing(5), problem(4), learning(4), algorithms(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-11-30
Volume 10, Issue 4, Year 2010, On page(s): 81 - 86
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.04013
Web of Science Accession Number: 000284782700013
SCOPUS ID: 78649707649

Abstract
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Suggesting more efficient driving routes generate benefits not only for individuals by saving commute time, but also for society as a whole by reducing accident rates and social costs by lessening traffic congestion. In this paper, we suggest a new route search algorithm based on a genetic algorithm which is more easily installable into mutually communicating car navigation systems, and validate its usefulness through experiments reflecting real-world situations. The proposed algorithm is capable of searching alternative routes dynamically in unexpected events of system malfunctioning or traffic slow-downs due to accidents. Experimental results demonstrate that our algorithm searches the best route more efficiently and evolves with universal adaptability.


References | Cited By  «-- Click to see who has cited this paper

[1] Explanation of Transport Protocol Experts Group, Dec. 2, 2008, Available: Temporary on-line reference link removed - see the PDF document

[2] E. Moon, "The Introduction of Digital Multimedia Broadcasting in Korea," July 2006, Available: Temporary on-line reference link removed - see the PDF document

[3] D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Upper Saddle River, NJ: Addison-Wesley, 1989.

[4] C. W. Ahn, R. S. Ramakrishna, and C. G. Kang, "A New Genetic Algorithm for Shortest Path Routing Problem," IEEE Transactions on Evolutionary Computation, Vol. 6, No. 6, Dec. 2002.

[5] J. Pearl, Heuristics: Intelligent Search Strategies for Computer Problem Solving. Upper Saddle River, NJ: Addison-Wesley, 1984.

[6] A. Nagurney and Q. Qiang, "Robustness of transportation networks subject to degradable links," A Letters Journal Exploring the Frontiers of Physics, 68001-p1-p6, 2007.

[7] I. H. Jung, D. H. Son, "Survey of Highway Business Effect," Korea Research Institute for Human Settlements, 1995.

[8] E. W. Dijkstra, "A Note on Two Problems in Connexion with Graphs," Numerische Mathematik, Vol. 1, pp. 269-271, 1959.
[CrossRef] [SCOPUS Times Cited 17528]


[9] Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction. MIT Press, Cambridge, MA, 1998.

[10] G. Harik, E. Cant¢u-Paz, D. E. Goldberg, and B. L. Miller, "The Gambler's ruin problem, genetic algorithms, and the sizing of populations," Evol. Comput., Vol. 7, No. 3, pp. 231-253, 1999.
[CrossRef] [PubMed] [Web of Science Times Cited 183] [SCOPUS Times Cited 217]


[11] M. Munetomo, Y. Takai, and Y. Sato, "A Migration Scheme for the Genetic Adaptive Routing Algorithm," IEEE International Conference on Systems, Man, and Cybernetics, pp. 2774-2779, 1998.
[CrossRef]


[12] J. Inagaki, M. Haseyama, and H. Kitajima, "A Genetic Algorithm for Determining Multiple Route and Its Applications," Proceedings of IEEE International Symposium on Circuits and Systems, pp. 137-140, 1999.
[CrossRef]


[13] Y. Leung, G. Li, and Z. B. Xu, "A genetic algorithm for the multiple destination routing problems," IEEE Trans. EVol. Comput., Vol. 2, pp. 150-161, Nov. 1998.
[CrossRef] [SCOPUS Times Cited 91]


[14] Z. Xiawei, C. Changjia, and Z. Gang, "A genetic algorithm for multicasting routing problem," in Proc. Int. Conf. Communication Technology (WCC-ICCT 2000), pp. 1248-1253, 2000.

[15] N. Shimamoto, A. Hiramatsu, and K. Yamasaki, "A dynamic routing control based on a genetic algorithm," in Proc. IEEE Int. Conf. Neural Networks, pp. 1123-1128, 1993.
[CrossRef] [SCOPUS Times Cited 54]


[16] D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley.

[17] X. Hue, "Genetic algorithms for optimization: Background and applications," Edinburgh Parallel Computing Centre, Univ. Edinburgh, Edinburgh, Scotland, Ver 1.0, Feb. 1997.

[18] Sebastian Zander, Thuy Nguyen, and Grenville Armitage, "Automated traffic classification and application identification using machine learning," in Proc. of IEEE Conf. on Local Computer Networks, pp. 250-257, 2005.
[CrossRef] [SCOPUS Times Cited 456]




References Weight

Web of Science® Citations for all references: 183 TCR
SCOPUS® Citations for all references: 18,346 TCR

Web of Science® Average Citations per reference: 10 ACR
SCOPUS® Average Citations per reference: 966 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-03-27 19:07 in 43 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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