The chilling train is a very important section for ethylene plants, as its design and operation significantly influence energy consumption and product loss rates. In this paper, a systematic methodology for the optimal design and operation of a chilling train system has been presented. A multiobjective mixed-integer nonlinear programming (MINLP) model has been developed, which aims at minimizing the ethylene loss rate and the exergy-accounted energy consumption, meanwhile maximizing the hydrogen recovery rate. Also presented are the technologies for obtaining reliable thermodynamic properties based on rigorous simulation and the methods for removing redundant variables for MINLP model simplification. On the basis of the methodology, the optimal design and operating conditions of a chilling train system can be simultaneously achieved. A real case study has demonstrated the efficacy of the developed methodology. The results show that the optimized chilling train system has better economic performance than the current system.