School of Engineering, Department of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran.
College of Engineering, Department of Civil Engineering, Boise State University, Boise, ID, USA.
Environ Monit Assess. 2019 Jun 26;191(7):468. doi: 10.1007/s10661-019-7557-2.
In face of the new climate and socio-environmental conditions, conventional sources of water are no longer reliable to supply all water demands. Different alternatives are proposed to augment the conventional sources, including treated wastewater. Optimal and objective allocation of treated wastewater to different stakeholders through an optimization process that takes into account multiple objectives of the system, unlike the conventional ground and surface water resources, has been widely unexplored. This paper proposes a methodology to allocate treated wastewater, while observing the physical constraints of the system. A multi-objective optimization model (MOM) is utilized herein to identify the optimal solutions on the pareto front curve satisfying different objective functions. Fuzzy transformation method (FTM) is utilized to develop different fuzzy scenarios that account for potential uncertainties of the system. Non-dominated sorting genetic algorithm II (NSGA-II) is then expanded to include the confidence level of fuzzy parameters, and thereby several trade-off curves between objective functions are generated. Subsequently, the best solution on each trade-off curve is specified with preference ranking organization method for enrichment evaluation (PROMETHEE). Sensitivity analysis of criteria's weights in the PROMETHEE method indicates that the results are highly dependent on the weighting scenario, and hence weights should be carefully selected. We apply this framework to allocate projected treated wastewater in the planning horizon of 2031, which is expected to be produced by wastewater treatment plants in the eastern regions of Tehran province, Iran. Results revealed the efficiency of this methodology to obtain the most confident allocation strategy in the presence of uncertainties.
面对新的气候和社会环境条件，传统的水资源已不再可靠，无法满足所有的用水需求。因此，提出了不同的替代方案来增加常规水源，包括处理后的废水。与传统的地下水和地表水不同，通过优化过程，从多个系统目标的角度出发，为不同的利益相关者优化和客观地分配处理后的废水，这种方法还没有得到广泛的探索。本文提出了一种分配处理后废水的方法，同时遵守系统的物理约束。本文利用多目标优化模型（MOM）来识别帕累托前沿曲线上的最优解，这些解满足不同的目标函数。模糊变换方法（FTM）用于开发不同的模糊情景，以考虑系统的潜在不确定性。然后，将非支配排序遗传算法 II（NSGA-II）扩展到包括模糊参数的置信水平，从而生成几个目标函数之间的权衡曲线。随后，使用偏好排序组织方法对每个权衡曲线上的最优解进行指定（PROMETHEE）。在 PROMETHEE 方法中对标准权重的敏感性分析表明，结果高度依赖于加权方案，因此应谨慎选择权重。我们将此框架应用于分配 2031 年规划期内预计将由伊朗德黑兰省东部地区废水处理厂产生的预测处理后废水。结果表明，在存在不确定性的情况下，该方法能够获得最可信的分配策略。
