多目标模糊优化问题的神经网络解法

Fuzzy Multi-objective Optimization Based on Neural Networks

基于函数联接神经网络 ,提出了一种解决工程结构多目标模糊优化问题的新算法。该算法以设计人员对目标函数值的满意程度作学习样本 ,采用神经网络取代传统的隶属度函数 ,从而较好地解决了隶属函数的描述问题。在解决多目标模糊优化问题中 ,该算法较传统算法具有更大的灵活性。

Based on the functional link network, a new algorithm is proposed to solve the multi objective optimization problems in engineering structures. In the algorithm, the degress of designer's satisfaction are regarded as a sample set, and neural network is used to replace the traditional membership functions. The membership functions can be well described with the new method. This method is more flexible than the traditional ones in solving multi objective optimization problems.