Cutting Stock Problem (CSP) applied to Structural Optimization for the minimum waste cost

In this study, an optimization method to design simple truss structures for the evaluation of the optimal stock of existing elements is introduced. To achieve this goal, the well-known Bin Packing Problem (BPP) will be implemented within the structural optimization procedure. Specifically, among all the BPP variants, one of the most common applications in real-world cases is the Cutting Stock Problem (CSP) in which the objective is to produce d(j) copies of each item type j by employing the minimum number of bins. In the civil engineering field, structural optimization is often employed aiming to improve the load-bearing capacity of the structure itself, i.e. maximization of the performance ratio through the minimization of the structure weight. However, this goal doesn't guarantee maximum efficiency in terms of minimization of 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 and the best arrangement of bars whit the lowest cut-off waste is obtained for a 10-bar-truss case study. For completeness reasons, a comparison between the solution obtained by the classic minimum weight optimization problem and the stock-constrained one is discussed.