Abstract The large chilled water plants with multiple chillers were widely used at large-scale public since a reduced starting in-rush current and a reduced power cost under part load conditions. It is important that the cooling load should be allocated to individual chillers operating in order to optimize their aggregate COP of the multi-chiller system. In this paper, an optimization method was developed to optimize the load sharing strategies for a multiple-chiller system, based on the operational data of a multi-chiller system in a shopping mall. The first step was that using the Least Squares Method (LMS), the parameters of efficiency performance models of each chiller were identified based on the operational data of a multi-chiller system in a shopping mall. The second step is that a genetic algorithm (GA) was used to optimize the load sharing strategy for the multiple-chiller system, resulting in optimizing their aggregate COP of the multi-chiller system. Lastly, this optimization method developed was applied to control the multi-chiller system in the shopping mall under a typical summer day. The results that compared with the conventional control method, the optimization control method can reduce the energy consumption by 3511.26 kW*h in the summer typical day. It can seen that the optimization method developed in this paper can help reduce the energy consumptions of the multi-chiller system in the shopping mall. Moreover, there was a larger energy saving potential in summer.