An innovative approach for optimization of the hydrogen network in a refinery is presented. The optimization problem was formulated as a fuzzy-based multiobjective nonlinear programming (FMONLP), aiming at simultaneous minimization of the total annual cost and CO2 emission. This is achieved by defining an objective function with a weighted sum of the annual cost and CO2 emission. The weighting factors are considered as fuzzy parameters which are described based on the experts' experiences. The applicability of the proposed approach is illustrated by optimization of an Iranian refinery hydrogen network.