Outranking sorts the objective preferences, and utility function sorts the solution preferences.
Difficult to construct MATLAB program of the technique 5 Computational efforts Less (simple FGP models, No repetition of values, solution preferences of the decision vectors are not considered) Much (repetition of values, comparative complex FGP models, solution preferences of the decision vectors are considered).
In proposed modified FGP approach, solution preferences by the decision makers at each level are not considered and fuzzy goal for the decision vectors is defined using individual best solutions.
The proposed modified algorithm as well as MATLAB program simplifies the earlier algorithm on ML-LFPP by eliminating solution preferences by the decision makers at each level, thereby avoiding difficulties associate with multi-level programming problems and decision deadlock situation.
It is clear that both the approaches are close to one another but the modified methodology is efficient and requires less computations than earlier technique in terms of considering the solution preferences by the decision maker at each level.
To overcome such computational difficulties, we modified FGP approach for ML-LFPP in which solution preferences by decision maker at each level and sequential order of decision-making process in finding satisfactory solutions are not taken into account of proposed technique and we straightforwardly obtain compromise optimal solution of the problem with higher degree of membership function values.
Here, it is important to note that for simplicity of proposed technique and in order to avoid decision deadlock situation in the whole solution methodology, the solution preferences by the decision maker in terms of values of decision vector at each level with respect to the values of decision vector at lower levels are not considered.
In this paper, we proposed modified FGP approach for multi-level linear fractional programming problem (ML-LFPP) in which solution preferences by decision maker at each level and sequential order of decision-making process in finding satisfactory solutions are not taken into account of proposed technique.
Baky (2010) suggested two new techniques with FGP approach based on solution preferences by the decision maker at each level to solve new type of multi-level multi-objective linear programming (ML-MOLP) problems through the fuzzy goal programming (FGP) approach.
In particular, we show how to use the notion of forgetting to provide an elegant solution for preference elicitation in disjunctive logic programming.
