jahanshahloo has suggested a method for the solving linear programming problems with zero-one variables‎. ‎in this paper we formulate fully fuzzy linear programming problems with zero-one variables and a method for solving these problems is presented using the ranking function and also the branch and bound method along with an example is presented.

-A neural network approach for solving fuzzy linear programming problems is proposed in which fuzzy concepts are not used. This approach is totally based on the level-sum method introduced Pandian [11]. The nearest optimal solution of the fuzzy linear programming original problem can be obtained by the proposed approach. The large scale fuzzy linear programming problems can be solved efficientl...

‎we consider a linear programming problem in a general form and suppose that all coefficients may vary in some prescribed intervals‎. ‎contrary to classical models‎, ‎where parameters can attain any value from the interval domains independently‎, ‎we study problems with linear dependencies between the parameters‎. ‎we present a class of problems that are easily solved by reduction to the classi...

A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DMUs) to select the most advantageous weights in calculating their efficiency scores. This flexibility, on the other hand, deters the comparison among DMUs on a common base. For dealing with this difficulty and assessing all the DMUs on the same scale, this paper proposes using a multiple objective...

  We suggest a method for finding the non-dominated points of the production possibility set (PPS) with variable returns to scale (VRS) technology in data envelopment analysis (DEA). We present a multiobjective linear programming (MOLP) problem whose feasible region is the same as the PPS under variable returns to scale for generating non-dominated points. We demonstrate that Pareto solutions o...

‎We consider a linear programming problem in a general form and suppose that all coefficients may vary in some prescribed intervals‎. ‎Contrary to classical models‎, ‎where parameters can attain any value from the interval domains independently‎, ‎we study problems with linear dependencies between the parameters‎. ‎We present a class of problems that are easily solved by reduction to the classi...

In this paper, we study the classical sensitivity analysis when the right - hand – side vector, and the coefficients of the objective function are allowed to vary. 

Quadratic programming (QP) is an optimization problem wherein one minimizes (or maximizes) a quadratic function of a finite number of decision variable subject to a finite number of linear inequality and/ or equality constraints. In this paper, a quadratic programming problem (FFQP) is considered in which all cost coefficients, constraints coefficients, and right hand side are characterized by ...