Javascript must be enabled to continue!
EVALUATING PARETO FRONT WITH TOPSIS AND FUZZY TOPSIS FOR LITERACY RATES IN ODISHA
View through CrossRef
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).
Title: EVALUATING PARETO FRONT WITH TOPSIS AND FUZZY TOPSIS FOR LITERACY RATES IN ODISHA
Description:
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).
Related Results
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Abstract. Fuzzy Inference System requires several stages to get the output, 1) formation of fuzzy sets, 2) formation of rules, 3) application of implication functions, 4) compositi...
Generated Fuzzy Quasi-ideals in Ternary Semigroups
Generated Fuzzy Quasi-ideals in Ternary Semigroups
Here in this paper, we provide characterizations of fuzzy quasi-ideal in terms of level and strong level subsets. Along with it, we provide expression for the generated fuzzy quasi...
ω – SUBSEMIRING FUZZY
ω – SUBSEMIRING FUZZY
Mapping ρ is called a fuzzy subset of an empty set of S if ρ is the mapping from S to the closed interval [0,1]. A fuzzy subset ρ introduced into this paper is a fuzzy subset of se...
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
Background Several scholars defined the concepts of fuzzy soft set theory and their application on decision-making problem. Based on this concept, researchers defined the generalis...
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
Background Several scholars defined the concepts of fuzzy soft set theory and their application on decision-making problem. Based on this concept, researchers defined the generalis...
FUZZY‐FUZZY AUTOMATA
FUZZY‐FUZZY AUTOMATA
Based on the concept of fuzzy sets of type 2 (or fuzzy‐fuzzy sets) defined by L. A. Zadeh, fuzzy‐fuzzy automata ate newly formulated and some properties of these automata are inves...
Fuzzy Chaotic Neural Networks
Fuzzy Chaotic Neural Networks
An understanding of the human brain’s local function has improved in recent years. But the cognition of human brain’s working process as a whole is still obscure. Both fuzzy logic ...
Comparison of single server queuing performance measures using fuzzy queuing models and intuitionistic fuzzy queuing models with infinite capacity
Comparison of single server queuing performance measures using fuzzy queuing models and intuitionistic fuzzy queuing models with infinite capacity
This paper presents boundless capacity, one server’s fuzzy and intuitionistic fuzzy queuing models. This study’s primary objective is to demonstrate and compare the performance of ...

