Although formal simulation-optimization approaches have been shown to be able to identify near-optimal outcomes for a range of stormwater management problems, stakeholder acceptance of these solutions can be problematic, especially if there is a lack of familiarity with the optimization processes and simulation model used to arrive at these solutions. To address this problem, a portfolio optimization problem formulation is introduced that allows stormwater best management practices (BMPs) to be evaluated by stakeholders before the portfolio selection process. This enables the search space to be constrained before the BMP optimization process, ensuring that model results are transparent and only represent solutions that are trusted by experienced practitioners. This has the effect of reducing reliance on simulation-optimization involving complex stormwater simulation models, and increasing buy-in to the optimization results. The portfolio optimization formulation is applied to a catchment management problem in Australia, using a typical many-objective optimization approach including visualization techniques.

尽管已经证明正式的模拟优化方法能够针对一系列雨水管理问题识别出接近最佳的结果，但利益相关者对这些解决方案的接受可能会出现问题，尤其是在对优化过程和模拟模型缺乏了解的情况下。用于得出这些解决方案。为了解决这个问题，引入了投资组合优化问题的表述，使利益相关者可以在投资组合选择过程之前对雨水最佳管理实践（BMP）进行评估。这样可以在BMP优化过程之前限制搜索空间，从而确保模型结果是透明的，并且仅表示有经验的从业者信任的解决方案。这样可以减少对复杂雨水模拟模型的模拟优化的依赖，并增加对优化结果的支持。使用典型的多目标优化方法（包括可视化技术），将投资组合优化公式应用于澳大利亚的流域管理问题。