Using Trapezoidal Intuitionistic Fuzzy Number to Find Optimized Path in a Network
Author(s) -
P. Jayagowri,
G. Geetha Ramani
Publication year - 2014
Publication title -
advances in fuzzy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 19
eISSN - 1687-711X
pISSN - 1687-7101
DOI - 10.1155/2014/183607
Subject(s) - path (computing) , node (physics) , arc (geometry) , computer science , arc length , fuzzy logic , fuzzy number , mathematical optimization , decision maker , path length , data mining , mathematics , artificial intelligence , operations research , fuzzy set , computer network , geometry , structural engineering , engineering
In real life, information available on situations/issues/problems is vague, inexact, or insufficient and so the parameters involved therein are grasped in an uncertain way by the decision maker. But in real life such uncertainty is unavoidable. One possible way out is to consider the knowledge of experts about the parameters involved as fuzzy data. In a network, the arc length may represent time or cost. In Relevant literature reports there are several methods to solve such problems in network-flow. This paper proposes an optimized path for use in networks, using trapezoidal intuitionistic fuzzy numbers, assigned to each arc length in a fuzzy environment. It proposes a new algorithm to find the optimized path and implied distance from source node to destination node
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