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Time Probabilistic Vehicle Optimal Route using Ant Colony Algorithm

Volume 13, Number 6, October 2017 - Paper 18  - pp. 975-984
DOI: 10.23940/ijpe.17.06.p18.975984

Ming Fua, Jian Zhoua,*, Lifang Wangb

aSchool of management science and engineering, Anhui University of Finance&Economics, Bengbu 233030, Anhui, China
bSchool of international trade and economics, Anhui University of Finance&Economics, Bengbu 233030, Anhui, China

(Submitted on April 29, 2017; Revised on August 12, 2017; Accepted on September 23, 2017)

Abstract:

Vehicle routing problem is one of hot issues in the past decade; the paper proposes an important variant of vehicle routing problem, which we name time probabilistic vehicle routing problem. We find the time spent on the road from point A to point B always changes because of dynamic road condition, dynamic weather et al. However, the probability is certain that the vehicle can travel from point A to Point B within certain time intervals. Ant colony algorithm is an efficient distributed algorithm, and has been widely used in various fields. The ant colony algorithm is introduced to obtain the optimal solution by observing the characteristics of the problem. The Ants also search for the next transfer node according to probability in ant colony algorithm. Ant colony algorithm can solve this kind of problem effectively.

 

References: 13

    1. B. Bedregal, R. Reiser, H. Bustince, C. L. Molina, V. Torra, "Aggregation functions for typical hesitant fuzzy elements and the action of automorphisms", Information Sciences, vol. 255, no. 1, pp. 82-99, 2014.
    2. N. Chen, Z. S. Xu, M. M. Xia, "Interval-valued hesitant preference relations and their applications to group decision making", Knowledge-Based Systems, vol. 37, no. 2, pp. 528-540, 2013.
    3. B. Farhadinia, "A theoretical development on the entropy of interval-valued fuzzy sets based on the intuitionistic distance and its relationship with similarity measure", Knowledge-Based Systems, vol. 39, no. 2, pp. 79-84, 2013.
    4. Z. J. Fu, F. G. Huang, K. Ren, J. Weng, C. Wang, "Privacy-preserving smart semantic search based on conceptual graphs over encrypted outsourced data", IEEE Transactions on Information Forensics and Security, vol. 12, no.8, pp. 1874-1884, 2017.
    5. Z. J. Fu, K. Ren, J. G. Shu, X. M. Sun, F. X. Huang, "Enabling personalized search over encrypted outsourced data with efficiency improvement", IEEE Transactions on Parallel and Distributed Systems, vol. 27, no. 9, pp. 2546–2559, 2016.
    6. Z. J. Fu, X. L. Wu, C. W. Guan, X. M. Sun, K. Ren, "Toward efficient multi-keyword fuzzy search over encrypted outsourced data with accuracy improvement", IEEE Transactions on Information Forensics and Security, vol. 11, no. 12, pp. 2706-2716, 2016.
    7. H. C. Liao, Z. S. Xu, "A VIKOR-based method for hesitant fuzzy multi-criteria decision making", Fuzzy Optimization & Decision Making, vol. 12, no. 4, pp. 373-392, 2013.
    8. H. C. Liao, Z. S. Xu, X. J. Zeng, "Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making", Information Sciences, vol. 271, no. 3, pp. 125-142, 2014.
    9. H. C. Liao, Z. S. Xu, X. J. Zeng, J. M. Merigó, "Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets", Knowledge-Based Systems, vol. 76, no. 1, pp. 127-138, 2015.
    10. J. J. Peng, J. Q. Wang, X. H. Wu, H. Y. Zhang, X. H. Chen, "The fuzzy cross-entropy for intuitionistic hesitant fuzzy sets and their application in multi-criteria decision-making", International Journal of Systems Science, vol. 46, no. 13, pp. 1-16, 2014.
    11. H. Wang, "Extended hesitant fuzzy linguistic term sets and their aggregation in group decision making", International Journal of Computational Intelligence Systems, vol. 8, no. 1, pp. 14-33, 2015.
    12. J. Q. Wang, Z. Q. Han, H. Y. Zhang, "Multi-criteria group decision-making method based on intuitionistic interval fuzzy information", Group Decision and Negotiation, vol. 23, no. 4, pp. 715-733, 2014.
    13. J. Q. Wang, D. D. Wang, H. Y. Zhang, X. H. Chen, "Multi-criteria outranking approach with hesitant fuzzy sets", OR Spectrum, vol. 36, no. 4, pp. 1001-1019, 2014.

       

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