Evaluating decision making units under uncertainty using fuzzy multi-objective nonlinear programming

TL;DR

This paper introduces a fuzzy multi-objective nonlinear programming approach to evaluate decision-making units under uncertainty, considering fuzzy data in objectives and constraints, and compares it with existing models using a numerical example.

Contribution

It presents a novel fuzzy DEA model that incorporates fuzzy objectives and constraints within a multi-objective nonlinear programming framework.

Findings

The proposed model effectively evaluates DMUs under uncertainty.

Comparison shows advantages over existing fuzzy DEA models.

Numerical example demonstrates practical applicability.

Abstract

This paper proposes a new method to evaluate Decision Making Units (DMUs) under uncertainty using fuzzy Data Envelopment Analysis (DEA). In the proposed multi-objective nonlinear programming methodology both the objective functions and the constraints are considered fuzzy. The coefficients of the decision variables in the objective functions and in the constraints, as well as the DMUs under assessment are assumed to be fuzzy numbers with triangular membership functions. A comparison between the current fuzzy DEA models and the proposed method is illustrated by a numerical example.