EVALUATING PARETO FRONT WITH TOPSIS AND FUZZY TOPSIS FOR LITERACY RATES IN ODISHA

Authors

  • Mr. UditNarayan Kar Department of Computer Science Saurashtra University Rajkot, Gujarat, India
  • Miss Arunima Kar 3Department of Computer Science and Information Technology Institute of Technical Education and Research Bhubaneswar, Odisha, India
  • Miss. Anyatama Kar Department of Computer Science and Information Technology Institute of Technical Education and Research Bhubaneswar, Odisha, India

DOI:

https://doi.org/10.53555/eijse.v1i2.40

Keywords:

MCDM, TOPSIS, Fuzzy TOPSIS, FPIS, FNIS, VIKOR, Odisha

Abstract

In engineering design and manufacturing, conflicting disciplines and technologies are always involved in the design process. Decision making is the process of finding the best option among the feasible alternatives. Multi Criteria Decision Making (MCDM) methods can help decision makes to effectively deal with such situation and make wise design decision to produce an optimized design. There are varieties of existing MCDM methods, thus the selection of the most appropriate method is critical since the use of inappropriate methods often causes misleading decision process. The MCDM methods are based on aggregating function representing closeness to ideal, TOPSIS is one of the most efficient methods. And also it can be fuzziffied which gives rise to a new method called Fuzzy TOPSIS. Fuzzy TOPSIS is a new method for MCDM and very easy to understand and it is originated in the compromise programming method. Here we have adapted the Fuzzy TOPSIS method and we have arranged the multiple numbers of criteria using Knapsack algorithm and created a Pareto Front with the help of non-dominated sorting method. Then we have ranked all the alternatives with classical Fuzzy TOPSIS method. In this paper the literacy rate of Odisha (a state of India) has been analyzed by using normal TOPSIS and fuzzy TOPSIS methods and the comparative results are given. The data sets considered in this paper are the real time data given by National Census (20002013).

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Published

2015-06-27