many ranking methods have been proposed so far. however, there is yet no method that can always give a satisfactory solution to every situation; some are counterintuitive, not discriminating; some use only the local information of fuzzy values; some produce different ranking for the same situation. for overcoming the above problems, we propose a new method for ranking fuzzy quantities based on ...

We present a new model and a new approach for solving fuzzylinear programming (FLP) problems with various utilities for the satisfactionof the fuzzy constraints. The model, constructed as a multi-objective linearprogramming problem, provides flexibility for the decision maker (DM), andallows for the assignment of distinct weights to the constraints and the objectivefunction. The desired solutio...

This paper proposes a compromise model, based on a new method, to solve the multiobjectivelarge scale linear programming (MOLSLP) problems with block angular structureinvolving fuzzy parameters. The problem involves fuzzy parameters in the objectivefunctions and constraints. In this compromise programming method, two concepts areconsidered simultaneously. First of them is that the optimal alter...

In an earlier work [Pop and Stancu Minasian, 2008], we proposed a method of solving the fully fuzzified linear fractional programming (FFLFP) problem. In this paper, we propose another method of solving the FFLFP problem. First, analogically using the Charnes-Cooper method, we transform the linear fractional programming problem into a linear one. Next, problem of maximizing a function with tria...

In real-life situations, the project manager must handle multiple conflicting goals and these conflicting goals are normally fuzzy owing to information is incomplete and unavailable. This study develops a two-phase fuzzy goal programming (FGP) method for solving the project management (PM) decision problems with multiple goals in uncertain environments. The original multi-objective linear progr...

In multiple objective programs [MOP], application functions are established to measure the degree of fulfillment of the decision maker’s requirements (achievement of goals, nearness to an ideal point, satisfaction, etc.) about the objective functions (see e.g. [7, 24]) and are extensively used in the process of finding ”good compromise” solutions. In [6] we demonstrated that the use of interdep...