In this work, the methanol synthesis on a commercial industrial catalyst in a novel cylindrical radial flow packed-bed reactor is investigated. The adiabatic and nonadiabatic cylindrical radial flow reactors were proposed and modeled in this research. The proposed configuration has been compared with conventional reactor for methanol production. It leads to higher methanol production and lower pressure drop, with the same catalyst consumption. Furthermore, the results show that the nonadiabatic radial flow packed-bed reactor has a higher methanol content compared with the adiabatic one. The improvement in methanol production was studied by optimizing the essential parameters such as inlet temperatures of the feed and cooling water as well as the number of cooling tubes. The nonlinearity and complexity of the reactor models make the traditional optimization methods ineffective and improbable. Therefore, the process was optimized by genetic algorithm (GA) method, which is one of the most powerful methods. The optimum values for the number of cooling tubes, feed and cooling water temperatures were 308, 507.6 K, and 522.43 K, respectively. The optimization results showed that a new reactor design could be proposed to reduce the cost of methanol synthesis.