Journal
JOURNAL OF HYDRO-ENVIRONMENT RESEARCH
Volume 21, Issue -, Pages 76-85Publisher
ELSEVIER
DOI: 10.1016/j.jher.2018.08.002
Keywords
Urban Stormwater Drainage Systems; Optimization; AMALGAM; Hypervolume Indicator; Tehran
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Design/rehabilitation of urban stormwater drainage systems has become a challenging issue due to increasing frequency and severity of floods in urbanized areas. Optimization frameworks can provide a proficient computational tool for stormwater management. In this study, using four different optimization algorithms and EPA-SWMM (Environmental Protection Agency-StorrnWater Management Model) software, a coupled numerical and optimization model was developed to rehabilitate the drainage system in eastern Tehran, Iran. The current drainage network suffers from a significant lack of hydraulic capacity. Thus, combinations of relief tunnels and/or storage units were evaluated and optimal rehabilitation strategies were suggested according to minimizing conflicting objective functions of costs and flooding. Results have revealed that AMALGAM (A Multi-Algorithm, Genetically Adaptive Multi-objective) outperformed three other algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm-II), NSHS (Non-dominated Sorting Harmony Search), and NSDE (Non-dominated Sorting Differential Evolution) for the evaluation of rehabilitation of Urban Stormwater Drainage Systems (USDSs) in terms of convergence and diversity criteria.
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