Combinatorial optimization approach for the efficient reuse of <scp>RC</scp> components

Abstract The reuse of reinforced concrete (RC) components from deconstructed buildings offers a promising approach to reduce the environmental impact of new constructions. However, it represents a complex combinatorial optimization problem to efficiently place the available modules, which vary in geometry and load‐bearing capacity, into new structures while maximizing their utilization. This paper proposes a two‐stage optimization method to enable the reuse of arbitrary RC modules. First, an agent‐based model is employed to rapidly explore feasible geometric combinations of modules and preselect suitable placements based on a target span length. Second, metaheuristic optimization algorithms, namely Simulated Annealing and Tabu Search, are adapted to maximize the utilization of the modules' load‐bearing capacity while ensuring global structural integrity. The methods are demonstrated on a case study of assembling a three‐span continuous beam. Lacking real data of dismantled RC elements, a construction kit of 100 modules with varying cross‐sectional properties and material parameters is artificially sampled. The results show the agent‐based preselection effectively finds viable geometric combinations, while the metaheuristics converge on optimized module placements with up to 88% utilization on average. The proposed approach provides a computational framework to enable the direct reuse of structural concrete components, supporting the design of low‐carbon circular buildings.