Abstract

In recent years, there has been an increasing focus on adopting circular approaches within the construction sector, particularly reusing building components in new projects. Facilitating design for reuse can significantly expand the scope of deconstruction and reuse efforts. Unlike conventional structural design, which assumes an unlimited supply of standardized components and follows a straightforward process of geometric design, structural analysis, and member sizing, reusing structural components introduces unique challenges. With limited component availability and compatibility constraints (e.g., member length and cross-section requirements), conventional design methods often fall short, leading to time-consuming trial-and-error processes, infeasible design iterations, or solutions with limited reuse potential. Despite growing interest, research in this area remains limited and often focuses on isolated criteria such as minimizing material waste or embodied impacts, without offering a comprehensive framework that balances environmental and economic considerations while explicitly accounting for inventory constraints. Additionally, conventional approaches often rely on traditional deterministic optimization methods, which can restrict exploration of complex design spaces and diverse trade-off solutions.
To address these challenges, this research proposes an optimization framework that leverages parametric modelling and generative design using genetic algorithms to streamline the design of steel structures with reused components. The framework integrates structural verification, inventory preparation, reuse filtering and assignment, and objective function(s) evaluation in a unified workflow. It supports both single-objective decision-making using an aggregated R-Score and multi-objective optimization using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to minimize energy consumption, CO₂ emissions, cost, and material waste. The framework is demonstrated through two steel truss case studies: (i) a controlled scenario using a hypothetical inventory to validate the workflow and (ii) a realistic scenario using a recovered inventory of reused components from the Champlain Bridge, evaluated under different reuse conditions (maximum reuse and reuse compatibility). The results show that the proposed approach can efficiently generate structurally feasible and inventory-compliant design alternatives and provide clear insight into trade-offs to support reuse-oriented decision-making.