In this paper, a Multi-criteria De Novo Linear Programming (F-MDNLP) problem has been developed under consideration of the ambiguity of parameters. These Fuzzy parameters are characterized by Fuzzy numbers. A Fuzzy goal Programming approach is applied for the corresponding multi-criteria De Novo linear Programming (   MDNLP) problem by defining suitable membership functions and aspiration levels. The advantage of the approach is that the decision maker's role is only the specification of the level and hence evaluate the   efficient solution for limitation of his/ her incomplete knowledge about the problem domain. A numerical example is given for illustration.

In this study, we discussed a Fuzzy Programming approach to bi-level linear Programming problems and their application. Bi-level linear Programming is characterized as mathematical Programming to solve decentralized problems with two decision-makers in the hierarchal organization. They become more important for the contemporary decentralized organization where each unit seeks to optimize its own objective. In addition to this, we have considered Bi-Level Linear Programming (BLPP) and applied the Fuzzy Mathematical Programming (FMP) approach to get the solution of the system. We have suggested the FMP method for the minimization of the objectives in terms of the linear membership functions. FMP is a supervised search procedure (supervised by the upper Decision Maker (DM)). The upper-level decision-maker provides the preferred values of decision variables under his control (to enable the lower level DM to search for his optimum in a wider feasible space) and the bounds of his objective function (to direct the lower level DM to search for his solutions in the right direction).

There are many cases that a nonlinear fractional Programming, generated as a result of studying fractional stochastic Programming, must be solved. Sometimes an approximate solution may be sufficient enough to start a new process of calculations. To this end, this author introduces a new linear approximation technique for solving a fractional chance constrained Programming (CCP) problem. After introducing the problem, the equivalent deterministic form of the fractional nonlinear Programming problem is developed. To solve the problem, a Fuzzy goal Programming model of the equivalent deterministic form of the fractional chance constrained Programming is provided and then the process of defuzzification and linearization of the problem is started. A sample test problem is solved for presentation purposes.

We are concerned with solving Fuzzy Flexible Linear Programming (FFLP) problems. Even though, this model is very practical and is useful for many applications, but there are only a few methods for its situation. In most approaches proposed in the literature, the solution process needs at least, two phases where each phase needs to solve a linear Programming problem. Here, we propose a method to solve the given problem in just one phase using only one problem. Furthermore, using our approach, sensitivity analysis of Fuzzy Flexible Linear Programming (FFLP) problem is simpler. For an illustration of our method, some numerical examples given. In particular, a practical problem is formulated and is solved by our method and several other methods and the obtained results are compared.