What is it about?

In this study, we develop an extended multi-objective mixed integer programming (EMOMIP) approach for water resources management under uncertainty, in which the parameters are fuzzy random variables while the decision variables are interval variables. This method can satisfy both optimistic and pessimistic decision makers simultaneously. Finally, a real example is given to explain the proposed method.

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Why is it important?

-An extended multi-objective formulation is proposed to the water resource problem through possibility theory -Fuzzy chance-constrained programming is used to convert the problem to the deterministic mixed integer programming. -Some alternatives are applied for retrieving water shortages. -The real case study in Tabriz city, Iran is considered in this paper. -The results show the better and acceptable performance of the proposed method.


Writing this article was a great pleasure as it has co-authors with whom I have had long standing collaborations. To emphasize the implementation of this study, a case study of the water resources management in an area of Tabriz city, an urban area in East Azarbaijan province near Lake Urmia, has been considered. Climate change and over exploitation of groundwater and drought effects in recent years have led to a decrease in surface currents and extra-capacity pressures on the groundwater resources in the region, which has caused a sharp decrease in groundwater levels in the region and adverse effects on the water resources entering the Lake Urmia. The continuation of such a process in the exploitation of groundwater resources and the allocation of land to high water needs will increase the drying rate, the water quality reducing, undesirable water of most wells in the region and the critical condition of Lake Urmia, and will impose additional costs on the competing users of the region. In this study, the optimal water allocation of this area is investigated.

Dr. javad nematian
University of Tabriz

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This page is a summary of: An extended multi-objective mixed integer programming for water resources management through possibility theory, Ecological Informatics, November 2019, Elsevier, DOI: 10.1016/j.ecoinf.2019.100992.
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