Issue: 2022/Vol.32/No.1, Pages 49-71

AN ALGORITHM FOR QUADRATICALLY CONSTRAINED MULTI-OBJECTIVE QUADRATIC FRACTIONAL PROGRAMMING WITH PENTAGONAL FUZZY NUMBERS

Vandana Goyal, Namrata Rani, Deepak Gupta

Full paper (PDF)    

Cite as: V. Goyal, N. Rani, D. Gupta. An algorithm for quadratically constrained multi-objective quadratic fractional programming with pentagonal fuzzy numbers. Operations Research and Decisions 2022: 32(1), 49-71. DOI 10.37190/ord220103

Abstract
This study proposes a methodology to obtain an efficient solution for a programming model which is multi-objective quadratic fractional with pentagonal fuzzy number as coefficients in all the objective functions and constraints. The proposed approach consists of three stages. In the first stage, defuzzification of the coefficients is carried out using the mean method of alfa-cut. Then, in the second stage, a crisp multi-objective quadratic fractional programming model (MOQFP) is constructed to obtain a non-fractional model based on an iterative parametric approach. In the final stage, this multi-objective non-fractional model is transformed to obtain a model with a single objective by applying the epsilon-constraint method. This final model is then solved to get the desired solution. In addition, an algorithm and flowchart expressing the methodology are provided to present a clear picture of the approach. Finally, a numerical example is given to illustrate the complete approach.

Keywords: multiobjective quadratic fractional programming model (MOQFPM), pentagonal fuzzy number (PFN), mean method of alfa-cut, parametric approach, epsilon-constraint method

Received: 11 June 2021    Accepted: 7 March 2022