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This paper explores the design approach of multi-atrium configurations to improve the energy efficiency of shopping malls in cold climates. A typical building prototype in northern China was considered, and an artificial neural network (ANN)-based metamodel was developed with four design variables: the atrium area ratio ( r ), atrium number ( n ), distance between adjacent atriums ( d0 ), and distance between atrium and façade wall ( d1 ). The proposed metamodel was used for sensitivity analysis (SA) and building design optimization (BDO) to understand the performance of multi-atrium configuration. The SA indicates that the contribution of the design variables to the building energy efficiency follows the order  r  &gt;  d0  &gt;  n  &gt;  d1 , and there are interactions between variables  r  and  n . The BDO demonstrates that it is beneficial for energy efficiency to incorporate more atrium areas, appropriate atrium sizes, larger distances between adjacent atriums, and more west-facing atriums.

Multi-atrium configuration design for energy efficiency in shopping malls: an ANN-based metamodel for sensitivity analysis and design optimization