MULTIOBJECTIVE OPTIMIZATION FUZZY TECHNIQUES BASED ON FUNCTIONAL-LINK NEURAL NETWORK

摘要

The principle of solving multiobjective optimization problems with fuzzy sets theory isrnstudied. However, membership function is the key to introduce the fuzzy sets theory to multiobjectivernoptimization, it is difficult to determine membership functions in engineering applications. On the basisrnof the strong capability of interpolation of functional-link neural network, discrete membershiprnfunctions are used as sample training data. When the network converges, the continuous membershiprnfunctions implemented with the network. Membership functions based on functional-link neuralrnnetworks have been used in multiobjective optimization. An example is given to illustrate the method.