Solving the fuzzy shortest path problem using multi-criteria decision method based on vague similarity measure

  • Authors:

  • Yaling Dou;Lichun Zhu;Ho Simon Wang

  • Affiliations:

  • College of Mathematics & Computer, Hunan Normal University, Changsha 410081, PR China and College of Computer Science & Technology, Huazhong University of Science & Technology, Wuhan 430074, PR Ch ...;School of Computer Science, University of Windsor, Ontario, Canada N9B 3P4;School of Intellectual Property Rights, Zhongnan University of Economics and Law, Wuhan 430074, PR China

  • Venue:
  • Applied Soft Computing
  • Year:
  • 2012

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Abstract

Many researchers have focused on the fuzzy shortest path problem in a network with non-deterministic information due to its importance to various applications. The goal of this paper is to select the shortest path in multi-constrained network using multi-criteria decision method based on vague similarity measure. In our approach, each arc length represents multiple metrics. The multi-constraints are equivalent to the concept of multi-criteria based on vague sets. We propose a similarity measure of vague sets in which the positive constraints and the negative constraints are defined. Furthermore, the procedures are developed to obtain the ''best'' and ''worst'' ideal paths. We evaluate similarity degrees between all candidate paths and two ideal paths with the proposed similarity measure. Through comparing the relative degrees of paths, it is shown that the path with the largest relative degree is the shortest path. Finally, we conduct two sets of numerical experiments-using Matlab to verify the feasibility and correctness of the proposed algorithm and developing a routing decision simulation system (RDSS) to demonstrate that the proposed approach is reasonable and effective.