This study aimed to develop a hybrid simulation-optimization model to find optimal strategies for the rehabilitation of urban drainage systems. The HEC-HMS was used for rainfall-runoff analysis and the EPA-SWMM model to hydraulically route the floods in urban channels. A combination of EPA-SWMM with a new developed multi-objective evolutionary algorithm (MOEA), called non-dominated sorting enhanced differential evolution (NSEDE), was used to optimize the size of flood walls, cross-structures and detention ponds, with the objective of minimizing the rehabilitation costs and runoff surcharge. NSEDE exhibited better performance in terms of convergence and solution diversity compared to three well-known MOEAs. Comparison of the model outputs with the rehabilitation plan of Tehran municipality demonstrated the superiority of the optimum designs. At the same level of cost and flooding with respect to the Tehran municipality plan, the optimum designs reduced the cost of rehabilitation by 61.7% and network flooding by 37.5%.

本研究旨在开发一种混合模拟优化模型，以找到修复城市排水系统的最佳策略。HEC-HMS 用于降雨径流分析，EPA-SWMM 模型用于对城市河道中的洪水进行水力路由。EPA-SWMM 与新开发的多目标进化算法 (MOEA) 相结合，称为非支配分类增强差分进化 (NSEDE)，用于优化防洪墙、交叉结构和滞留池的大小，其中目标是尽量减少恢复成本和径流附加费。与三个著名的 MOEA 相比，NSEDE 在收敛性和解决方案多样性方面表现出更好的性能。模型输出与德黑兰市恢复计划的比较证明了优化设计的优越性。