In response to the current issues of high energy consumption, environmental pollution, and safety hazards associated with the vinyl chloride distillation process, this study has developed a sustainable, economically energy-efficient, and safe multi-objective optimization method for the vinyl chloride distillation process. Based on the actual operation of the vinyl chloride distillation process in enterprises, this research employs the Non-dominated Sorting Genetic Algorithm III (NSGA-III) to optimize key parameters of the distillation operation, aiming to achieve multiple objectives such as improving product quality, reducing energy consumption, decreasing CO2 emissions, and enhancing process safety. The safety performance of the optimized scheme was comprehensively evaluated through simulation with Aspen Plus V14 software, combined with Hazard and Operability (HAZOP) qualitative risk analysis and quantitative risk analysis based on Aspen Plus. Through comparative analysis with the original design scheme, the following conclusions were drawn: all optimization plans (A, B, C, D) are superior to the original design to varying degrees. Further research revealed that as the number of iterations of the genetic algorithm increases, the optimization plans have significantly improved in terms of multi-objective performance, highlighting the importance of adequate iteration in the process of finding the optimal solution. The outcomes of this study not only provide an effective strategy for the optimization of the vinyl chloride distillation process but also offer a theoretical basis and practical guidance for the green development and safe production in the chemical industry.