Multi-objective Optimization of Methane Producing UASB Reactor Using a Combined Pareto Multi–objective Differential Evolution Algorithm (CPMDE)

Abstract

Multi–objective optimization of an operating industrial wastewater treatment plant was carried out using combined Pareto multi–objective differential evolution (CPMDE) algorithm. The algorithm combines methods of Pareto ranking and Pareto dominance selections to implement a novel selection scheme at each generation. Modified methane generation and the Stover–Kincannon kinetic mathematical models were formulated for optimization. The conflicting objective functions that are optimized in this study include, maximization of volumetric methane production rate in the biogas produced at a lower hydraulic retention time and optimum temperature; minimization of effluent substrate concentration in order to meet the environmental discharge requirements based on the standard discharge limit, and finally, the minimization of biomass washout from the reactor. Wastewater flow rate, hydraulic retention time, efficiency of substrate utilization within the reactor, influent substrate concentration and operational temperature are the important decision variables related to this process. A set of non-dominated solutions with the high methane production rate at lower biomass and almost constant solution for the effluent concentration was obtained for the multi-objective optimization problem. In this study, the simulation results showed that the CPMDE approach can generate a better Pareto-front of the selected problem and its ability to solve unconstrained, constrained and real-world optimization problem was also demonstrated.