An Integrated Fuzzy Simulation-Optimization Model for Supporting Low Impact Development Design under Uncertainty
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Seeking cost-effective design of urban hydrological facilities and drainage systems is an important task for many city planners. However, such a process has always been complicated with intrinsic uncertainties. This work presented an integrated fuzzy simulation-optimization model (FSOM) for supporting Low Impact Development (LID) design under model uncertainties. Various LID implementation schemes involving green roof, bio-retention cell, and permeable pavement were simulated through an urban hydrological model. Three model parameters were assumed as fuzzy sets. In a case study, fuzzy simulation (FS) and genetic algorithm (GA) were employed to search the optimal schemes of LIDs under various confidence levels of satisfying flood control constraints. Comparison of FSOM to traditional deterministic and stochastic models were also carried out. It was shown that FSOM could offer a flexible way of defining and assessing uncertainties associated with hydrological modeling and generate solutions that were comparable to those from either deterministic or stochastic models. However, FSOM also showed limitation of high computational requirement.
KeywordsUrban flood Low impact development Optimization Chance-constrained programming Fuzzy simulation Hydrological modeling uncertainties
Fuzzy simulation-optimization model
Low impact development
Storm water management model
Urban drainage system
This project was supported by Research Grant (M4082254.030) from School of Civil and Environmental Engineering, Nanyang Technological University, Singapore.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
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