Hybrid Algorithm Performance With Varying Population Size for Multi-objective Optimisation of In-situ Bioremediation of Groundwater


In-situ bioremediation of groundwater is one of the remediation technique applied for cleaning groundwater at its site. Cost of remediation and remaining concentration of contaminant are the main conflicting objectives to be decided during remediation period of groundwater. Multi objective optimisation is one of the best techniques to obtain Paretos for the conflicting objectives. In this study metaheuristic hybrid algorithm has been used to obtain Paretos for in-situ bioremediation of groundwater. Further, the performance of Paretos obtained with varying population size has been evaluated. The results indicate that too small or too large population size does not give well spaced Paretos. Only the population size in specific range shows better performance in the present study for groundwater remediation. The cost analysis of in-situ bioremediation based on the Paretos obtained from proposed hybrid algorithm shows that percentage increase in cost increases as the clean up standard of groundwater increases.