Abstract: The aim of this research is to solve the problems such as low crop yield and high energy consumption in greenhouse production that is caused by unreasonable heating value. Crop and temperature models were built by analyzing the relationships among the external environment, temperature, and crops. A crop-temperature coupling model with crop growth and heating energy consumption as evaluation indicators was built. In order to optimize the heating value, the crop-temperature coupling models were solved using collections of external environment information and applications of imperialist competitive algorithms. And the method of optimizing heating value was verified by experiments. The experiments showed that optimizing heating value could effectively reduce energy consumption and ensure crop growth, thereby maximizing revenue. Compared with the method of greenhouse heat preservation, the accumulation of dry weight and fresh weight increased by 64.3% and 70.6%, respectively. The crop income increased by 35.5% per square meter by optimizing heating value. Compared with the method of heating control, the accumulations of dry weight and fresh weight were reduced by 11.5% and 9.6% per square meter, but it saved 51.3% of the heating energy consumption and increased 16.1% of the crop income per square meter. The above data proved the feasibility of the research and provided an effective control method for heating for the greenhouse production manager.