Resilience-oriented optimization of prefabricated construction supply chain based on improved multi-objective artificial electric field algorithm

Purpose The development of prefabricated construction (PC) is often hindered by inadequate planning, inefficient delivery, and poor resilience. This study demonstrates that proactive planning can significantly improve the efficiency and resilience of the prefabricated construction supply chain (PCSC), helping operators effectively avoid supply chain risks. Design/methodology/approach This study proposes an optimization model that considers both production and transportation processes. An improved multi-objective artificial electric field algorithm (IMOAEFA) is introduced, incorporating the principles of non-dominated sorting, crossover-based local search strategies, and external archives to optimize the PCSC planning, aiming to balance cost, carbon emissions and resilience. Resilience is quantitatively measured through inventory buffering capacity. The performance of IMOAEFA is then evaluated through computer simulation experiments. Findings The results indicate that the proposed method can effectively quantify resilience, balance competing objectives to support decision-making and enhance resilience by optimizing the sequence of production and transportation. Furthermore, the IMOAEFA demonstrates significant improvements in convergence, distribution, uniformity and spatial exploration, overcoming the limitations of traditional metaheuristic algorithms. Originality/value This study reveals the trade-offs among economic, environmental, and resilience objectives within the PCSC. The findings equip planners with the necessary tools to tailor supply chain strategies to specific project requirements. More importantly, this study emphasizes that proactive planning can better avoid supply chain risks. When the supply chain faces unforeseen disruptions, this solution offers more recovery opportunities. Additionally, these findings provide guidance for future metaheuristic algorithms addressing similar issues.