## 4 Conclusions  
This study highlights the effectiveness of a multi-objective optimization framework that integrates LCC with technological and operational resilience. The proposed approach provides a valuable decision-making tool for addressing extreme hydrological events in densely populated urban areas. The key findings of this research are as follows:  
1. Integration of GREI and GI. Coupled strategies that optimize the integration of GREI and GI outperform standalone GREI solutions. These integrated systems offer enhanced economic viability and resilience, particularly in mitigating the impacts of hydrological adversities;
2. Performance gains in GGI. While implementing GGI with selected resilience preferences may slightly increase LCC, the enhanced Oper-R provided by GGI significantly improves overall system performance compared to GREI-only networks;
3. Resilience of decentralized systems. Decentralized GGI systems demonstrate superior flexibility and resilience to extreme storm events, even when substantial damage occurs to GREI components. This highlights their robustness and adaptability in addressing severe climatic challenges;
4. Effectiveness of bioretention cells. For equivalent footprint areas, BCs outperform PPs in attenuating surface runoff, making them particularly suitable for densely urbanized areas. Their application has high potential for increasing pervious surface areas, contributing to improved stormwater management;
5. Critical component analysis for enhanced reliability. The failure of critical drainage system components can lead to severe flooding. To ensure long-term system reliability and resilience, it is essential to assess the most severe threats and their consequences throughout the infrastructure's lifespan using critical component analysis, even for low-probability extreme events. This research contributes a comprehensive and adaptable optimization approach that supports resilient, cost-effective, and context-sensitive urban stormwater management planning. It provides a valuable decision-making tool for city planners, engineers, and policymakers seeking to navigate the increasing complexity of stormwater management under climate change. Future studies could further refine this framework by incorporating broader environmental indicators, additional GI types, and more advanced optimization techniques to address the multifaceted challenges of urban stormwater systems. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15073852/s1](https://www.mdpi.com/article/10.3390/app15073852/s1)]([https://www.mdpi.com/article/10.3390/app15073852/s1](https://www.mdpi.com/article/10.3390/app15073852/s1)), Table S1: Characteristics of sub-catchments in the Storm Water Management Model (SWMM); Table S2 Design parameters of permeable pavement (PP) and bioretention cells (BCs) in SWMM; Figure S1: Spatial representation and identification of network elements in optimized grey infrastructure-only (GREI-only) networks across varying degrees of decentralization (DDL). Key elements include pipe networks, flow outlets, and drainage configurations, highlighting structural adaptations under different DDL scenarios; Figure S2: Spatial arrangement of selected grey-green infrastructure (GGI) systems following trade-off optimization. The configurations illustrate the allocation of green infrastructure elements (e.g., bioretention cellsand permeable pavements) integrated with optimized grey infrastructure networks to balance cost, resilience, and hydrological performance. Conceptualization, M.W. and L.W. ; methodology, [PERSON] ([PERSON]), Z.X. and M.W. ; software, [PERSON] ([PERSON]), [PERSON] and [PERSON]. ([PERSON]); validation, L.W. ; formal analysis, M.W. and L.W. ; investigation, [PERSON] ([PERSON]), [PERSON] and [PERSON]. ([PERSON]); resources, M.W. and L.W. ; data curation, [PERSON], [PERSON] ([PERSON]) and L.W. ; writing--original draft preparation, M.W. and L.W. ; writing--review and editing, M.W. ; visualization, [PERSON] ([PERSON]), [PERSON] and [PERSON].