Robust decision support for seawater desalination system management under consideration of environmental pollution...

Seawater desalination is one of the most popular options to alleviate the water crisis worldwide. Effective management of a seawater desalination system is thus critical. In this study, a fuzzy robust optimization programming model, named FROP, has been proposed to provide robust decision support for seawater desalination management under consideration of environmental pollution control and uncertainty. The major contributions of the proposed FROP model include the following: (1) it is designed for effectively addressing the interactions among seawater desalination development, desalted water distribution, water requirement, and control of environmental pollutant emission within an integrated seawater desalination system; (2) it is an effective decision support tool for decision-makers to provide robust planning strategies through simultaneously considering the optimality robustness and feasibility robustness; (3) it can quantify imprecise and vague uncertainties related to the various aspects of the integrated seawater desalination system expressed as fuzzy parameters; and (4) it can address the tradeoffs among meeting the economic objective and environmental protection requirements and guaranteeing the stability of the system (i.e., risk of violating system constraints) under uncertainty. In order to demonstrate its applicability, the FROP model is applied in a hypothetical seawater desalination management system which is consistent with management schemes in practices. The results indicate that despite a higher total system cost, the management objective and environmental requirements are met, whereas a lower total system cost results in a higher risk of violating the constraints and the possibility of destabilizing the system. The FROP model is helpful for decision-makers to develop robust and cost-effective management schemes for seawater desalination systems under different economic and environmental constraints and complex uncertain conditions.