Stock Optimization of Naturally Curved Wood Logs on Freeform Truss Structures

This paper presents an optimization method for incorporating discarded naturally curved wood logs onto a freeform gridshell with a predefined topology. Though still little explored, the research field of reusing structural elements is experiencing increasing attention owing to its significant potential to reduce the environmental impact of building design. However, several constraints must be considered as the optimal structure depends on stock availability and the corresponding geometry and material properties of that given stock. Therefore, the focus is on determining the best configuration of stock elements considering the defined design objectives and constraints. The proposed method is a top-down approach, as the global topology of the structure is predetermined. Multi- objective optimization is conducted using the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and a modified genetic algorithm with permutation encoding in the form of ordered crossover and scramble mutation. Furthermore, this paper introduces a Team-Based Repair (TBR) algorithm that increases the likelihood of each solution being valid for analysis. The performance of the optimization method is demonstrated on a curved gridshell structure, and the effect of the different design objectives and stock sizes on the final design is analyzed and discussed.