Graduate Student Research Seminar Day 鈥� Nov 19, 2025
You are cordially invited to the Graduate Student Research Seminar of the Department of Industrial Engineering.
Date: Wednesday, Nov 19, 2025
Time: 11:30 - 12:00 pm AST
In Person:听Room B227, Sexton Campus
Online:听罢别补尘蝉
Meeting ID: 230 342 974 279 4
Passcode: Wc3vg9MC
(NOTE:听 Students are reminded that they must attend in person if they are planning to put this toward their Seminar course requirements.)
Schedule:
1130-1155 |
Angela Amegboleza, PhD Candidate Modelling and Optimization of Water Resource Management in Artisanal and Small-Scale Mining |
Abstracts:
Modelling and Optimization of Water Resource Management in Artisanal and Small-Scale Mining
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Angela Amegboleza, PhD Candidate
Artisanal and small-scale mining (ASM) has been identified as one of the most common threats to freshwater systems in resource-rich areas such as sub-Saharan Africa. Informal mining activities discharge untreated effluents, including mercury, cyanide, and heavy sediments, into rivers and streams, posing systemic threats to ecological integrity, community health, loss of aquatic biodiversity and water security. Existing research has largely been investigative, focusing more on environmental assessment rather than prescriptive planning tools capable of reconciling two or more objectives under uncertainty. In this study we adopted a multi-objective Mixed-Integer Linear Programming (MO-MILP) model to support the formulation of sustainable strategies for water management in ASM contexts by looking at environmental, economic, social, and cultural factors within a quadruple-bottom-line (QBL) of sustainability perspective. The model minimizes the cumulative cost of water-system operation, contaminant exposure, social inequity, and culture disruption under technical and policy constraints. We generalize the approach using Two-stage Stochastic analysis to model hydrological and contaminant randomness, and robust analysis to hedge against ambiguity under data scarcity conditions. Scenario and sensitivity analyses are used to further stress-test facility-siting, infrastructure-deployment, and equity-target thresholds under baseline, drought, and high-demand conditions. The contributions are theoretical in that it provides multi-objective optimization by combining robust and stochastic analysis, practically through the provision of a decision support tool for policy makers and development organisations to devise strategies for water governance in ASM that is resilient, fair, and culturally sensitive.
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Contact Person:
Hamid Afshari, Ph.D., P.Eng.
email: hamid.afshari@dal.ca听