S. Narayanamoorthy

Work place: Department of Applied Mathematics, Bharathiar University,Coimbatore – 46, India

E-mail: snm_phd@yahoo.co.in


Research Interests: Combinatorial Optimization


S. Narayanamoorthy was born in Tamilnadu, India in 1979. He received the B.Sc., M.Sc., M.Phil., & Ph.D., degrees from Loyola College(Autonomous),Chennai, India, in 1999 , 2001, 2002 and 2008 respectively. In 2009, he joined the Bharathiar University, Coimbatore, Tamilnadu, India, as an Assistant Professor, Department of Applied Mathematics. His activities currently focus on Applications of Fuzzy Mathematics (Social Problem). His research interest includes Fuzzy Optimization, Fuzzy Differential Equations and Fuzzy Graphs.

Author Articles
A Method for Solving Fuzzy Transportation Problem (FTP) using Fuzzy Russell’s Method

By S. Narayanamoorthy S.Saranya S.Maheswari

DOI: https://doi.org/10.5815/ijisa.2013.02.08, Pub. Date: 8 Jan. 2013

The basic transportation problem was originally developed by Hitchcock. In the literature several methods are proposed for solving Fuzzy transportation problem. In this paper, we propose a new algorithm called Fuzzy Russell’s method for the initial basic feasible solution to a Fuzzy transportation problem. To examine the proposed method a numerical example is solved. Fuzzy numbers may be normal or abnormal, triangular or trapezoidal or any LR fuzzy number. We can use this proposed method for any kind of Fuzzy numbers.

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Adaptation of Induced Fuzzy Cognitive Maps to the Problems Faced by the Power Loom Workers

By S. Narayanamoorthy S. Kalaiselvan

DOI: https://doi.org/10.5815/ijisa.2012.09.10, Pub. Date: 8 Aug. 2012

The Indian textile industry has a significant presence in the economy as well as in the international textile economy. In this research Paper we study the socio economic problems faced by power loom workers in Avinashi in Tamilnadu, India, using Induced Fuzzy Cognitive Maps (IFCMs). We have interviewed 50 households in the study area using a linguistic questionnaire. As the problems faced by them at large, involved so much of feelings and uncertainties. We felt it to fit to use fuzzy theory in general and induced fuzzy cognitive maps in particular. For IFCMs is the best suited tool when the data is an unsupervised one.

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