This paper investigates the optimal control problem of vacuum gas oil catalytic cracking, a key process in petroleum refining for producing valuable fuel fractions. The reaction is highly complex and nonlinear, requiring precise control of key parameters such as reaction temperature and time. The optimal control task is reformulated as a nonlinear global optimization problem and solved using the modified Particle Swarm Optimization (PSO) algorithm. The proposed modifications enhance solution feasibility and practical implementation. Using this approach, we analyze the impact of temperature and reaction time on process efficiency under both fixed and optimized conditions. The results demonstrate that optimal parameter selection significantly improves conversion rates and product yield. The paper presents all numerical experiment results and implementation details.