Benefits of pre-screening on more efficient multi-objective optimization of blue-green and grey infrastructures for urban stormwater management

Blue-green-grey (hybrid) infrastructure is widely acknowledged as an effective solution for addressing urban floods due to its complementary characteristics. Optimization algorithms have been extensively used to optimize the layout of hybrid stormwater management by balancing economic and flood mitigation benefits. However, little is known about the impact of narrowing down the solution search space on the optimization results and the application of multi-stage optimization to expedite the process. To address these research gaps, we tested three strategies within a simulation-based optimization framework in a study catchment located in Guangzhou, China. The global strategy considers all possible hybrid solutions, whereas the guided strategy focuses on the most effective solutions identified by means of a pre-screening method, which produces a flood impact matrix. Additionally, a multi-stage "selective" optimization strategy involved independent optimization of sub-drainage networks with flood issues. Results showed that guided and selective strategies with a reduced search space can significantly reduce the computation time by at least 3 times and 10 times, respectively, while achieving comparable, if not better, optimization performance compared to the global strategy. Our findings support the benefit of pre-screening algorithms before layout optimization to not only speed-up optimization, but also considerably reduce unfeasible or impractical infrastructure options. Furthermore, multi-stage optimization can provide an efficient alternative for faster optimization, particularly in assessing large case studies.