Structural Optimization Through Cutting Stock Problem

In this study, a novel optimization method has been applied to a geodesic dome inspired by real-world similar structures in which the environmental and cost impact has been minimized by reducing raw materials at the production stage. To achieve this goal, the Cutting Stock Problem (CSP) has been embedded inside the global optimization procedure of the entire structure. The CSP is one of the most famous combinatorial optimisation problems in the (one-dimensional) bin packing problems (BPP) class. The main objective is to produce \(d_j\) copies of each item type j (i.e. elements of the structures with the same cross-sectional Area) by employing the minimum number of bins such that the total weight in any bin does not exceed the capacity. In the civil engineering field, the traditional approach to structural optimization aims to improve the load-bearing capacity and the global performance of the structure itself. This includes, for instance, the maximization of the performance ratio through the minimization of the structure weight. However, this goal doesn’t guarantee maximum efficiency in reusing structural elements and minimising waste during the industrial production phase. To overcome these limits, authors propose a stock-constrained structural optimization in which a heuristic search technique is adopted in order to find the best spatial arrangement of elements composing the structure whit the lowest cut-off waste. Finally, considerations have been discussed by comparing the solution obtained by the traditional weight-minimization approach and the stock-constrained one.