Initially, the techniques to construct unilateral and bilateral nonlinear membership functions involved in fuzzy programming are introduced. Motivated by readily solving nonlinear fuzzy programming problems, this paper subsequently presents novel approaches to convert the nonlinear membership functions to piecewise linear ones. Therein, Gaussian integral functions are employed to calculate the discrete points, which are then offered to decision makers for benchmark options to build the piecewise linear membership functions. Finally, the formulations of the corresponding fuzzy programming are presented, along with a numerical example studied to demonstrate the effectiveness of the contribution.%首先给出了模糊规划中单、双边非线性隶属函数的构建技术.为了解决非线性模糊规划的求解困难问题,进一步提出了一种针对这两类非线性隶属函数进行分段线性化的方法,由高斯取整函数计算出非线性隶属函数的离散点,再根据决策者选择的基准点得到分段线性的隶属函数.构建了相应的模糊规划的规范求解形式,并对数值实例进行了测试,验证了其有效性.
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