The relationship between sensitivity analysis and fuzzy logic in multiple objective decision problems: de novo programming application

De Novo Programming is used for developing a design of an optimal system instead of optimizing a given system. This design is built considering the budget constraint. The amounts of the constraints that are arranged by De Novo designs are used with a full capacity. By doing this higher achievement levels of the objective functions can be reached. As the classical optimization problems are modelled with crisp data, with the fuzzy logic approach the parameters are designed in an interval. By this modelling approach more flexible results can be obtained. When the De Novo model is handled in a fuzzy environment the model paramaters are composed of fuzzy numbers. Fuzzification is applied on all of the parameters and the budget constraint. This approach provides more flexible results than the classical De Novo Programming. In this study, De Novo Programming model is handled with a different perspective and a new model is proposed. There are two distinguishing properties of this model standing out. They are: 1. By developing a MOLP model with a unit price restriction, the coefficients of the objedtive functions, right hand side contraints and the range of the intervals of the unit prices are obtained with the sensitivity analysis. 2. These intervals are added to our proposed model and the budget is limited by using fuzzy number while the amounts of the raw materials are determined. Keywords: 1) Multiple Objective Decision Making, 2) Multiple Objective Linear Programming, 3) Compromise Programming, 4) Goal Programming, 5) De Novo Programming, 6) Fuzzy Set Theory, 7) Fuzzy De Novo Programming