This research has focused on modeling and optimization of a radial flow tubular reactor to produce methanol from synthesis gas (syngas) at steady state condition. A heterogeneous one-dimensional model is developed based on the material and energy balance laws to predict the performance of proposed radial flow configuration. To verify the accuracy of developed model, the simulation results of a conventional Lurgi type reactor are compared with the available plant data. In the optimization stage, methanol production capacity is maximized considering the feed temperature, cooling side temperature and feed pressure as decision variables using the genetic algorithm method. Then, the performance of optimized radial flow reactor is compared with the conventional radial flow configuration. The comparison between efficiency of optimized radial flow, conventional radial and axial flow reactors shows an acceptable enhancement in the syngas conversion to methanol and lower pressure drop in the optimized radial flow reactor.