Hybrid Fuzzy-Linear Programming Approach for Multi Criteria Decision Making Problems

TL;DR

This paper demonstrates how fuzzy linear programming enhances multi-criteria decision making in business by improving optimization results and satisfaction levels compared to traditional methods.

Contribution

It introduces a hybrid fuzzy-linear programming model for multi-criteria decision making and validates its effectiveness through a real manufacturing case study.

Findings

Fuzzy techniques outperform non-fuzzy methods in optimizing objectives.

Incorporating fuzziness in constraints and objectives improves decision satisfaction.

The proposed approach is effective in real-world manufacturing scenarios.

Abstract

The purpose of this paper is to point to the usefulness of applying a linear mathematical formulation of fuzzy multiple criteria objective decision methods in organising business activities. In this respect fuzzy parameters of linear programming are modelled by preference-based membership functions. This paper begins with an introduction and some related research followed by some fundamentals of fuzzy set theory and technical concepts of fuzzy multiple objective decision models. Further a real case study of a manufacturing plant and the implementation of the proposed technique is presented. Empirical results clearly show the superiority of the fuzzy technique in optimising individual objective functions when compared to non-fuzzy approach. Furthermore, for the problem considered, the optimal solution helps to infer that by incorporating fuzziness in a linear programming model either in constraints, or both in objective functions and constraints, provides a similar (or even better) level of satisfaction for obtained results compared to non-fuzzy linear programming.