NSPP: A Novel algorithm for neutrosophic shortest path problem

In current decade the researchers addressed uncertainty issues. It becomes major issues in case of an effective shortest path in the given network system. This work tried to introduce a mathematical model to characterize the uncertainty in network based on truth, falsity and indeterminacy using interval-valued membership values. The motive is to provide an improved algorithm for shortest path problem. The distance among one node to another node is ranked using interval-valued neutrosophic membership-values. A comparison of our proposed algorithm with that of existing approaches is also established which shows the advantages of new algorithm over the existing ones.

[1]  Tahir Mahmood,et al.  Similarity Measures for T-Spherical Fuzzy Sets with Applications in Pattern Recognition , 2018, Symmetry.

[2]  Abdollah Hadi-Vencheh,et al.  An extension principle based solution approach for shortest path problem with fuzzy arc lengths , 2017, Oper. Res..

[3]  Peide Liu,et al.  Maximizing deviation method for neutrosophic multiple attribute decision making with incomplete weight information , 2015, Neural Computing and Applications.

[4]  Yong Deng,et al.  Fuzzy Shortest Path Problem Based on Biological Method , 2012 .

[5]  Vicenç Torra,et al.  Hesitant fuzzy sets , 2010, Int. J. Intell. Syst..

[6]  Jun Ye,et al.  Vector Similarity Measures for Simplied Neutrosophic Hesitant Fuzzy Set and Their Applications , 2017 .

[7]  Florentin Smarandache,et al.  ROUGH NEUTROSOPHIC SETS , 2014 .

[8]  Stephan Dempe,et al.  Sensitivity Analysis for Fuzzy Shortest Path Problem , 2004, Fuzzy Days.

[9]  Florentin Smarandache,et al.  Shortest Path Problem under Bipolar Neutrosphic Setting , 2016 .

[10]  Florentin Smarandache,et al.  Shortest path problem in fuzzy, intuitionistic fuzzy and neutrosophic environment: an overview , 2019, Complex & Intelligent Systems.

[11]  Qing Wang,et al.  A Biologically Inspired Optimization Algorithm for Solving Fuzzy Shortest Path Problems with Mixed Fuzzy Arc Lengths , 2014, J. Optim. Theory Appl..

[12]  Vicenç Torra,et al.  On hesitant fuzzy sets and decision , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[13]  Homayun Motameni,et al.  Constraint Shortest Path Problem in a Network with Intuitionistic Fuzzy Arc Weights , 2018, IPMU.

[15]  Luige Vladareanu,et al.  Applying Dijkstra algorithm for solving neutrosophic shortest path problem , 2016, 2016 International Conference on Advanced Mechatronic Systems (ICAMechS).

[16]  Jun Ye,et al.  A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets , 2014, J. Intell. Fuzzy Syst..

[17]  Qaisar Khan,et al.  SOME AGGREGATION OPERATORS FOR BIPOLAR-VALUES HESITANT FUZZY INFORMATION BASED ON EINSTEIN OPERATIONAL LAWS , 2017 .

[18]  Florentin Smarandache,et al.  Interval Valued Bipolar Neutrosophic Sets and Their Application in Pattern Recognition , 2016 .

[19]  Florentin Smarandache,et al.  Energy and Spectrum Analysis of Interval Valued Neutrosophic Graph using MATLAB , 2019 .

[20]  Qaisar Khan,et al.  An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets , 2019, Neural Computing and Applications.

[21]  Keon-Myung Lee,et al.  Comparison of Interval-valued fuzzy sets, Intuitionistic fuzzy sets, and bipolar-valued fuzzy sets , 2004 .

[22]  Florentin Smarandache,et al.  The theory of neutrosophic cubic sets and their applications in pattern recognition , 2016, J. Intell. Fuzzy Syst..

[23]  F. Smarandache,et al.  Shortest Path Problem Under Interval Valued Neutrosophic Setting , 2018 .

[24]  Sankar Sahoo,et al.  Computation of Shortest Path in a Vague Network by Euclidean Distance , 2018, J. Multiple Valued Log. Soft Comput..

[25]  Florentin Smarandache,et al.  Cosine Similarity Measure of Interval Valued Neutrosophic Sets , 2014 .

[26]  F. Smarandache,et al.  The shortest path problem in interval valued trapezoidal and triangular neutrosophic environment , 2019, Complex & Intelligent Systems.

[27]  Ilanthenral Kandasamy,et al.  Double-Valued Neutrosophic Sets, their Minimum Spanning Trees, and Clustering Algorithm , 2018, J. Intell. Syst..

[28]  Rajshekhar Sunderraman,et al.  Single Valued Neutrosophic Sets , 2010 .

[29]  Florentin Smarandache,et al.  Bipolar neutrosophic sets and their application based on multi-criteria decision making problems , 2015, 2015 International Conference on Advanced Mechatronic Systems (ICAMechS).

[30]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[31]  Bing-Yuan Cao,et al.  A New Algorithm to Shortest Path Problem with Fuzzy Arc Lengths , 2016 .

[32]  Cengiz Kahraman,et al.  A novel interval-valued neutrosophic AHP with cosine similarity measure , 2018, Soft Computing.

[33]  Luige Vladareanu,et al.  Computation of shortest path problem in a network with SV-trapezoidal neutrosophic numbers , 2016, 2016 International Conference on Advanced Mechatronic Systems (ICAMechS).

[34]  Xindong Peng,et al.  ALGORITHMS FOR INTERVAL NEUTROSOPHIC MULTIPLE ATTRIBUTE DECISION-MAKING BASED ON MABAC, SIMILARITY MEASURE, AND EDAS , 2018 .

[35]  Yanqing Zhang,et al.  Interval Neutrosophic Sets and Logic: Theory and Applications in Computing , 2005, ArXiv.

[36]  Qaisar Khan,et al.  SOME AGGREGATION OPERATORS FOR BIPOLAR-VALUED HESITANT FUZZY INFORMATION , 2017 .