This paper presents the development and the first application of an inexact quadratic programming (IQP) approach for sustainable water supply under multiple uncertainties. The developed IQP improves conventional nonlinear programming by tackling multiple uncertainties within an individual parameter; IQP is also superior to existing inexact methods due to its reflection of economies of scale and reduction of computational requirements. An interactive solution algorithm with high computational efficiency was also proposed. The application of IQP to long-term planning of a multi-source multi-sector water supply system demonstrated its applicability. The close reflection of system complexities, such as multiple uncertainties, scale economies and dynamic parameters, could enhance the robustness of the optimization process as well as the acceptability of obtained results. Corresponding to varied system conditions and decision priorities, the interval solutions from IQP could help generate a series of long-term water supply strategies under a number of economic, environmental, ecological, and water-security targets.
ABSTRACT. Traffic allocation planning is commonly required for mass evacuation management. It primarily relies on efficient coordination and appropriate utilization of roadway capacity and available traffic resources. However, traffic and evacuee information are usually difficult to be obtained and consequently of various uncertainties in data. Especially, stochastic information may often exist in evacuation management systems. In this study, a two-stage interval-stochastic evacuation management (TISEM) model was developed for supporting the evacuation planning under uncertainty, by which stochastic and interval evacuation information could be well reflected and communicated in the system. In addition, by adopting the proposed model, a case study abstracted from the City of Wuhan was introduced and solved through an interactive method. Results indicated that useful solutions for planning evacuation routes could be generated based on results of the model. As well, through the model, complex relationships between evacuation time, environmental influences and economic factors could be systematically analyzed. It demonstrated that the proposed TISP model is practical and applicable in real world, and is helpful for authorities to make decisions allocating vehicles before evacuation starts.
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