Sabina Yeasmin

Work place: Department of Mathematics, Gopalganj Science and Technology University, Gopalganj, Bangladesh

E-mail: syeasmin681@gmail.com

Website: https://orcid.org/0000-0002-2416-0450

Research Interests:

Biography

Sabina Yeasmin currently serves as an Assistant Professor in the Department of Mathematics at Gopalganj Science and Technology University, Gopalganj, Bangladesh. Her research interests include Ordinary Differential Equations (ODE), Partial Differential Equations (PDE), Linear Programming, Numerical Analysis, and Fluid Mechanics. In addition to her research, she actively teaches and supervises undergraduate students, fostering their academic growth. She has also contributed to the field through a publication.

Author Articles
Stochastic Model Including Refining Stage to Improve Water Supply System in Bangladesh

By Md. Asaduzzaman Nazrul Islam Sabina Yeasmin Md. Babul Hasan

DOI: https://doi.org/10.5815/ijmsc.2025.02.05, Pub. Date: 8 Jun. 2025

People around the world use fresh water daily for drinking, sanitation, and washing. At the same time, they discharge wastewater into canals, which can be harmful to both human health and the ecosystem of surface water sources. A significant amount of water is consumed for washing purposes. However, it is possible to disinfect and purify this large volume of wastewater for reuse. The process of treating used wastewater is known as refinement. This study aims to develop a two-stage stochastic recourse model that refines wastewater before it is released into the environment. The goal is to ensure that the refined wastewater does not harm the ecosystem. The treated water can then be repurposed for various secondary uses. The proposed model will account for uncertainties related to the availability of water from the supplying authority. To evaluate the effectiveness of this model, we will compare the costs of the water supply system both with and without refinement. The advantages of the proposed model will be assessed through calculations of the expected value of perfect information (EVPI), the value of the stochastic solution (VSS), the recourse solution (RS), the wait-and-see solution (WS), and the expected solution based on first-stage decisions (EEV). Additionally, a risk-averse (RA) optimization model will be used to analyze the sensitivity of system costs.

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