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.
%0 Journal Article
%1 https://doi.org/10.1002/suco.70126
%A Rose, Jannis
%A Forman, Patrick
%A Stieler, David
%A Menges, Achim
%A Mark, Peter
%D 2025
%J Structural Concrete
%K peer
%N n/a
%R https://doi.org/10.1002/suco.70126
%T Combinatorial optimization approach for the efficient reuse of RC components
%U https://onlinelibrary.wiley.com/doi/abs/10.1002/suco.70126
%V n/a
%X 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.
@article{https://doi.org/10.1002/suco.70126,
abstract = {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.},
added-at = {2025-05-12T10:55:18.000+0200},
author = {Rose, Jannis and Forman, Patrick and Stieler, David and Menges, Achim and Mark, Peter},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/295dc6d6f6e17509ba24a39eb6ed9e6ee/intcdc},
doi = {https://doi.org/10.1002/suco.70126},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/suco.70126},
interhash = {a7b71ab3aea39460a57e7a3e37da079e},
intrahash = {95dc6d6f6e17509ba24a39eb6ed9e6ee},
journal = {Structural Concrete},
keywords = {peer},
number = {n/a},
timestamp = {2025-05-12T10:55:18.000+0200},
title = {Combinatorial optimization approach for the efficient reuse of RC components},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/suco.70126},
volume = {n/a},
year = 2025
}
