基于灵敏性分析的模糊非线性规划方法

在求解含不确定性模型参数的模糊非线性规划问题时，一般会使用模糊区间较大的模糊参数，然而，这将会影响目标所能达到的满意度水平. 为此，论文提出采用灵敏性分析的方法研究模糊参数对目标的影响程度，找出严重制约优化目标满意度的模糊参数，通过减小其模糊区间而使问题的结果更加合理. 给出一种简单搜索算法确定模糊数的最佳取值区间，帮助决策者深入了解不确定性模型参数的性质. 通过一个数值实例详细阐述所提方法，验证了其有效性.

Sensitivity analysis based approach to fuzzy nonlinear programming

Traditionally, fuzzy numbers with wide spread are always employed to solve fuzzy nonlinear programming problems with uncertain model parameters, which undoubtedly degrades the satisfaction level of the objective. Motivated by this challenge, sensitivity analysis was suggested to investigate how the objective is influenced by every fuzzy number. After finding out those which make dramatic impacts on the objective and decreasing their fuzziness, the corresponding solutions would be more reasonable. A simple searching algorithm was introduced to specify the optimum spread of fuzzy numbers, helping decision makers make deep insight into the uncertain parameters. A numerical example was employed to demonstrate the effectiveness of the proposed approach.