Application of neutrosophic minimum spanning tree in electrical power distribution network. Issue 2 (27th April 2020)

• Record Type: Journal Article
• Authors: Liao, Xiao Qun; Su, Tong; Ma, Li
• Is Part Of: CAAI transactions on intelligence technology. Volume 5:Issue 2(2020)
• Page Start: 99
• Page End: 105
• Publication Date: 2020-04-27
• Subjects: distribution networks -- linear programming -- trees (mathematics) -- genetic algorithms -- set theory; real‐life problems -- neutrosophic MST problem -- linear programming model -- neutrosophic minimum spanning tree -- electrical power distribution network -- combinatorial optimisation problems -- graph theory -- triangular neutrosophic; B0250 Combinatorial mathematics -- B0260 Optimisation techniques -- B8120J Distribution networks; Artificial intelligence -- Periodicals; Computer science -- Periodicals; Artificial intelligence; Computer science; Electronic journals; Periodicals; 006.305
• DOI: 10.1049/trit.2019.0100
• Languages: English
• ISSNs: 2468-6557

Abstract

Abstract : The problem of finding the minimum spanning tree (MST) is one of the most studied and important combinatorial optimisation problems in graph theory. Several types of uncertainties exist in real‐life problems, which make it very hard to find the exact length of the arc. The neutrosophic set is an efficient tool to model and deal with the uncertainties in information due to inconsistent and indeterminate. In this study, the authors use triangular neutrosophic numbers to represent the edge weights of a neutrosophic graph for the MST problem in the neutrosophic environment. They call this problem a neutrosophic MST (NMST) problem. They formulate the NMST problem in terms of the linear programming model. Here, they introduce an algorithmic method based on a genetic algorithm for solving the NMST problem. They present the utility of triangular neutrosophic numbers as edge weights and their application in the electrical distribution network.