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The roof–column structural system is utilized for many engineering and architectural applications due to its structural efficiency. However, it typically requires column locations to be predetermined, and involves a tedious trial-and-error adjusting process to fulfil both engineering and architectural requirements. Finding efficient column distributions with the aid of computational methods, such as structural optimization, is an ongoing challenge. Existing methods are limited, with continuum methods involving the generation of undesired complex shapes, and discrete methods involving a time-consuming process for optimizing columns' spatial order. This paper presents a new optimization method to design the distribution of a given number of vertical supporting columns under a roof structure. A computational algorithm was developed on the basis of the optimality-criterion (OC) method to preserve and removed candidate columns pre-embedded with design requirements. Three substrategies are presented to improve optimizer performance. The effectiveness of the new method was validated with a range of roof–column structural models. Treating column locations as design variables provides opportunities to significantly improve structural performance. [ABSTRACT FROM AUTHOR]

The roof–column structural system is utilized for many engineering and architectural applications due to its structural efficiency. However, it typically requires column locations to be predetermined, and involves a tedious trial-and-error adjusting process to fulfil both engineering and architectural requirements. Finding efficient column distributions with the aid of computational methods, such as structural optimization, is an ongoing challenge. Existing methods are limited, with continuum methods involving the generation of undesired complex shapes, and discrete methods involving a time-consuming process for optimizing columns’ spatial order. This paper presents a new optimization method to design the distribution of a given number of vertical supporting columns under a roof structure. A computational algorithm was developed on the basis of the optimality-criterion (OC) method to preserve and removed candidate columns pre-embedded with design requirements. Three substrategies are presented to improve optimizer performance. The effectiveness of the new method was validated with a range of roof–column structural models. Treating column locations as design variables provides opportunities to significantly improve structural performance.