4.5 Article

An Application of Fully Intuitionistic Fuzzy Multi-objective Linear Fractional Programming Problem in E-education System

Journal

INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
Volume 24, Issue 8, Pages 3544-3563

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s40815-022-01348-2

Keywords

Multi-objective programming; Triangular intuitionistic fuzzy number; Goal programming; Linear fractional programming problem; Fuzzy mathematical programming

Funding

  1. Ministry of Human Resource Development, India
  2. Uttarakhand State Council for Science and Technology, Dehradun, India [UCS &T/R7D-19/20-21/19222/1]

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This article addresses a special class of non-linear programming problems, namely linear fractional programming problems with multiple objectives. It proposes a simple and computationally efficient approach to solve these problems, and demonstrates the feasibility and usefulness of the approach through a numerical illustration.
This article addresses a special class of non-linear programming problems, viz., linear fractional programming problems having multiple objectives. In solving the real-life linear fractional optimization problems, the ambiguity and hesitation in the decision are inherent and ever-present, therefore, it is perfectly viable to formulate and solve these optimization models using the intuitionistic fuzzy environment. The purpose of this study is to propose a simple and computationally efficient approach to obtain the solution of multiple objective linear fractional programming problems having all the decision variables and parameters expressed in terms of triangular intuitionistic fuzzy numbers. The proposed solution algorithm is primarily based on the goal programming approach, fuzzy-based linearization technique, and a membership function strategy. The original linear fractional programming problem is first converted to its equivalent deterministic/crisp multi-objective linear fractional optimization problem using the weighted goal programming methodology along with the linear membership technique to resolve the intuitionistic fuzzy constraints into the crisp one. Finally, the variable transformation technique for the under- and over-deviational variables of the goal programming model is employed to linearize all the fractions involved in the problem so as to convert the original problem to an equivalent linear optimization problem. Further, this linear programming problem can be solved using any available commercial packages. Moreover, a numerical illustration is provided to demonstrate the steps of the proposed technique followed by the analysis and solution of an E-education set-up problem. The discussion and comparisons of the practical case establish the relevancy and usefulness of the proposed model.

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