###### Abstract
Previous studies have demonstrated the efficacy of multi-objective optimization approaches in evaluating integrated stormwater management systems by accounting for hydrological performance, life cycle costs (LCC), and environmental impacts [11; 12]. [PERSON] et al. [13] proposed an enhanced simulation-optimization framework that modifies decision variables to simultaneously consider green and grey infrastructure design, focusing primarily on performance metrics such as flood reduction and cost. Similarly, [PERSON] et al. [14] employed agent-based modeling to evaluate the spatial deployment of six GI strategies in Newark, NJ, USA, accounting for social and economic co-benefits across private and public parcels. Nevertheless, these analyses have often overlooked critical factors such as time-dependent performance degradation, evolving maintenance requirements, and environmental variability, which introduce substantial uncertainties into the assessment and operational performance of GGI systems [15; 16]. Addressing these complexities is essential to advancing the reliability and robustness of GGI evaluations, ensuring their long-term efficacy under dynamic and uncertain conditions. Highlighting a paradigm shift in infrastructure design and management from traditional reliability-focused frameworks to resilience-oriented planning [17], this study underscores the critical need to address both technological resilience (Tech-R) and operational resilience (Oper-R) in stormwater systems. Technological resilience pertains to the physical robustness of stormwater infrastructure, enabling it to withstand environmental variability and extreme weather phenomena [18]. In contrast, operational resilience encompasses the functional stability of the system, encompassing key dimensions such as equipment durability, structural integrity under extraordinary loads, and the rapidity of post-event recovery [19]. Together, these resilience dimensions provide a comprehensive framework for enhancing the adaptability and reliability of stormwater systems in the face of growing climatic and urbanization challenges. Previous studies investigating the functional degradation of urban drainage systems have predominantly concentrated on Tech-R [20], largely due to its engineering-oriented parameters, which are more amenable to resolution through targeted investments and management strategies. However, research on Oper-R, particularly regarding secondary functionality losses following structural failures or gradual performance deterioration over time, remains comparatively underexplored [21]. While regression models have been utilized to estimate the likelihood of specific GREI failures [22], the performance of GI is inherently more uncertain due to its dynamic physical properties. Variables such as plant growth, sedimentation, clogging, blockages, and fluctuating surface and subsurface flow resistances contribute to substantial temporal and spatial variability [23]. Failure to account for these complexities risks the significant misrepresentation of GI effectiveness [24]. Consequently, holistic performance assessments must incorporate incremental and cumulative failure mechanisms for both Tech-R and Oper-R to ensure an accurate and comprehensive evaluation of system resilience. A comprehensive review of the existing literature highlights the pressing need for a robust optimization framework tailored to GGI systems, one that integrates Tech-R, Oper-R, and their synergistic contributions to overall system performance. The complexity of such optimization is compounded by the diverse array of performance metrics, decision-making processes across various developmental phases, and the interplay of technical, environmental, and social constraints. Real-world applications further necessitate the simultaneous optimization of multiple objectives including cost, reliability, Tech-R, and Oper-R, posing a formidable challenge for researchers and practitioners alike.