Study on Solution Method for a Numerical Fuzzy Programming Problem

Fuzzy programming, a well-known optimization problem in resource allocation and optimization decision etc, has become the hot research in academic circles and many application fields. In this paper, for the numerical fuzzy programming, we propose centralized quantification strategy for processing fuzzy objective function, and further give the concept of synthesizing effect functions for the overall consideration of the objective and constraint; Combing with fuzzy inequity degree and genetic algorithm, we establish numerical fuzzy programming model (denoted by BSE ID-FGM for short); Finally, we analyze the characteristic and effectiveness of this method through an example. All the results indicate that our method has better structural feature, and can effectively merge the decision preferences into the solution in quantification ways.