Generally, vagueness is modelled by a fuzzy approach and randomness by a stochastic approach. But in some cases, a decision maker may prefer using interval numbers as coefficients of an inexact relationship. In this paper, we define a linear programming problem involving interval numbers as an extension of the classical linear programming problem to an inexact environment. By using a new simple...

Quantifying extra functions, herein referred to as outcome over optimal solutions of an optimization problem can provide decision makers with additional information on a system. This bears more importance when the is subject uncertainty in input parameters. In this paper, we consider linear programming problems which parameters are described by real-valued intervals, and address range finding f...

In the present paper, a multiobjective linear programming problem under uncertainty, particularly when parameters are given in interval forms, is investigated. this case, it assumed that objective coefficients and constraints have arrived numbers. Considering suitable order relation for numbers, solution procedure dealing with such developed. A numerical example provided to illustrate efficienc...

In this paper, we considered a Stochastic Interval-Valued Linear Fractional Programming problem(SIVLFP). In this problem, the coefficients and scalars in the objective function are fractional-interval, and technological coefficients and the quantities on the right side of the constraints were random variables with the specific distribution. Here we changed a Stochastic Interval-Valued Fractiona...