This study aims to weigh the contradiction between energy consumption and cost in the design stage of low-temperature grain warehouse. To achieve this goal, a multi-objective optimization design platform for grain warehouse was constructed using the Rhino-Grasshopper parametric design tool. The optimization process comprises four stages: parametric modeling, setting of optimization variable parameters, establishment of the optimization objective, and multi-objective decision-making. Taking a grain warehouse in Henan region as an example, the platform was applied to obtain the optimal solution set for multi-objective optimization design. The results show that the optimized grain warehouse provides lower cooling energy consumption and cost than the reference buildings (Model1 and Model2). Compared with Model2, the refrigeration energy consumption is reduced by 70%, 63.33% and 38.67% for the energy-optimized, balanced and cost-optimized designs, respectively, and the whole life cycle cost is reduced by 32.92%, 49.43% and 53.29%, respectively.