A gradient algorithm for the analysis of pipe networks
Computer applications in water supply: vol. 1---systems analysis and simulation
Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Scour depth modelling by a multi-objective evolutionary paradigm
Environmental Modelling & Software
A DSS generator for multiobjective optimisation of spreadsheet-based models
Environmental Modelling & Software
Short communication: Topological clustering for water distribution systems analysis
Environmental Modelling & Software
Many-objective de Novo water supply portfolio planning under deep uncertainty
Environmental Modelling & Software
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Evolutionary optimization in uncertain environments-a survey
IEEE Transactions on Evolutionary Computation
Environmental Modelling & Software
Environmental Modelling & Software
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Decisions on protecting public health against drinking water systems contamination threats should be made with careful consideration of credibility of threat observations and adverse impacts of response on system serviceability. Decision support models are developed in this study to prepare water utility operators for making these critical decisions during the intense course of an emergency. A pressure-dependent demand model is developed to simulate the system hydraulics and contaminant propagation under pressure-deficit conditions that emerge after the response actions are executed. Contrary to conventional demand-driven models, this hydraulic analysis approach prevents potential occurrence of negative pressures during the simulation and may identify better response protocols through exploring a larger search space. Response mechanisms of contaminant containment and discharge are optimized using evolutionary algorithms to achieve public health protection with minimum service interruption. Sensitivity analyses are conducted to assess optimal response performance for varying response delay, number of hydrants, and intrusion characteristics. Different methods for quantifying impacts on public health and system serviceability are explored and the sensitivity of the optimal response plan to these different formulations is investigated. The simulation-optimization schemes are demonstrated and discussed using a virtual water distribution system.