Multi-objective Optimal Design of Groundwater Bioremediation Using Multi-objective and Ant Colony Algorithm

In situ bioremediation is one of the most regular technologies to clean up petroleum contaminated aquifers. Control process of such a complicated system is difficult and needs more than one management target. This study develops multi objective simulation/optimization model that consider cost and time of remediation process، and concentration violation from standard value as model objectives. For this propose two multi objective ant colony optimization (ACO) models have been developed، cost-time and cost-violations. The BIOPLUMEII model applies to simulate aquifer hydraulics and bioremediation. Injection rate of oxygen and nutrient، extraction rate in wells and well locations are decision variables. Simulated groundwater model is hypothetic and homogenous. For the case studies، the Pareto front is derived which enhances the decision maker to choose one which more suitable for him/her according to the priorities. The results of time-cost trade off curve showed minimum possible time for remediation process. Also، It was found maximum time for remediation before contamination plume reaches to downstream monitoring wells. The results of cost-violation trade off curve showed how to decrease cost of process with relaxation of standard concentration constraint. The following research shows the proposed multi objective models are useful for decision makers and also reveals the capability of ACO in multi objective optimization of groundwater bioremediation system design.