This paper presents a linear fractional programming approach for solving multi objective linear programming problem. We develop a model to solve multi objective linear programming problem into fractional programming problem and proposed a method for linearization of a fractional objective. In particular, we consider the optimization of ratio of profit and cash expenditure as fractional objectiv...

Traditional Data Envelopment Analysis (DEA) models evaluate the efficiency of decision making units (DMUs) with common crisp input and output data. However, the data in real applications are often imprecise or ambiguous. This paper transforms fuzzy fractional DEA model constructed using fuzzy arithmetic, into the conventional crisp model. This transformation is performed considering the goal pr...

In real-life scenarios, there are many mathematical tools to handle incomplete and imprecise data. One of them is the fuzzy approach. The main issue with addressing nonlinear interval programming (NIP) problems that optimal solution problem a decision made under uncertainty has risk not satisfying feasibility optimality criteria. Some strategies this kind using classical terminology such as fea...

This research article aims to study a multi-objective linear fractional programming (FMOLFP) problem having fuzzy random coefficients as well pseudorandom decision variables. Initially, the FMOLFP model is converted single objective (FLP) model. Secondly, we show that optimal solution of an FLP resolved into class relative (LP) As result, some theorems LP combined with series solutions problems...

A linearization technique is developed for multi-objective multi-quadratic 0-1 programming problems with linear and quadratic constraints to reduce it to multi-objective linear mixed 0-1 programming problems. The method proposed in this paper needs only O (kn) additional continuous variables where k is the number of quadratic constraints and n is the number of initial 0-1 variables.