In this research study, a fuzzy multi-objective optimization methodology is proposed for in-situ groundwater bioremediation utilizing the Graph Model for Conflict Resolution. In the current model, uncertainties in hydraulic conductivity and the ratio of transverse to longitudinal dispersivity of contaminants are considered using the Fuzzy Transformation Method (FTM). First, the BIOPLUME III simulation model is linked with a Non-dominated Sorting Genetic Algorithm II (NSGA-II) multi-objective optimization model to optimize a groundwater bioremediation system regarding conflicting viewpoints of decision makers. Then, the hydrogeological uncertainties of the groundwater bioremediation system are included in the proposed methodology using FTM. The three main objectives of the in-situ bioremediation optimization model are overall cost (well installation, treatment or pumping, and facility capital), the sum of contaminant concentration violating any standards, and contaminant plume fragmentation, which need to be minimized based on stakeholders’ preferences. Subsequently, GMCR II is utilized to resolve any conflicts between the perspectives of the stakeholders to achieve a compromise solution. The performance assessment results represent the ability of the proposed methodology for optimal in-situ groundwater bioremediation. Results show that the minimum fuzzy interval is 32.5%, and pertains to the overall cost of the bioremediation system in fuzzy α-cut levels of 0 and 0.5. Conversely, the maximum fuzzy interval is related to contaminant plume fragmentation in fuzzy α-cut levels of 0 and 0.5, and was found to be 95.1%.
- BIOPLUME III
- Fuzzy set theory
- Graph model
- In-situ bioremediation of groundwater
- NSGA-II multi-objective optimization model
ASJC Scopus subject areas
- Water Science and Technology