Here is a conference paper in which a neuro-fuzzy controller genetically enhanced was developed for a hexapod robot:

Pedro Ponce, Fernando Ramírez, Verónica Medina, "A novel neuro-fuzzy controller genetically enhanced using LabVIEW"; DOI: 10.1109/IECON.2008.4758186

I think following papers are addressed to similar  problems 

Melin, Patricia, and Oscar Castillo. "Intelligent control of complex electrochemical systems with a neuro-fuzzy-genetic approach." Industrial Electronics, IEEE Transactions on 48.5 (2001): 951-955.

Aguilar, Leocundo, Patricia Melin, and Oscar Castillo. "Intelligent control of a stepping motor drive using a hybrid neuro-fuzzy ANFIS approach." Applied Soft Computing 3.3 (2003): 209-219.

Mitra, Sushmita, and Yoichi Hayashi. "Neuro-fuzzy rule generation: survey in soft computing framework." Neural Networks, IEEE Transactions on 11.3 (2000): 748-768.

but I don't know how you want to use this three technique and what's your problem?

thanks for the suggestions.

I have already used ANFIS methodology for my problem- (packet delay calculation).

Now I would like to apply genetic on that. How can I combine ANFIS and genetic.

You can use genetic algorithms for finding the suitable coefficients of the output layer in ANFIS; or better, you can use genetic algorithms to optimize the number of neurons in ANFIS.

thanks for the answers.

I would like to know how genetic algorithm can be used to optimize the number of neurons in ANFIS.

can u plz suggest some papers or coding methods...