The overwhelming majority of wastewater treatment modelling considers the activated sludge process (ASP), globally the most common method of wastewater treatment. In this process, biomass (which is called activated sludge) suspended in the wastewater to be treated is cultivated and maintained in an aerated bioreactor. The wastewater is purified, i.e. organic carbon, nitrogen and phosphorus are removed, during its retention in the bioreactor. The bioreactor is followed by a clarifier basin, in which the biomass is separated by gravitational settling and returned to the bioreactor, and the treated wastewater is directed as overflow to further treatment or to discharge. Excess activated sludge is removed from the process and treated separately.
The wastewater treatment plant design has been previously considered by optimizing only one objective function, which in one way or another describes the costs of the process to be minimized. However, practical real-world optimization problems, like the ones in wastewater treatment, often have to be considered from many different perspectives. This gives rise to several conflicting evaluation criteria. When the optimization problem in question needs to be solved with respect to several conflicting criteria simultaneously, the concept of optimality needs to be redefined. When dealing with multiple conflicting objective functions, the solution can be seen as optimal when no objective function value can be improved without impairing any other objective. These optimal solutions are called Pareto optimal solutions or compromise solutions. Typical to these optimal solutions is that there usually are (infinitely) many of them and they all are mathematically equivalent. Solving these types of problems requires using the methods of multiobjective optimization.
To guarantee a final design which takes into account all the relevant criteria related to wastewater treatment, we propose an interactive design strategy that utilizes numerical simulation of wastewater treatment processes combined with an efficient interactive multiobjective optimization method. This enables the designer to simultaneously consider the process from different perspectives and optimally balance the final design between different conflicting design criteria.
In this paper, we concentrate on utilizing modern optimization techniques to provide decision support for the designer which helps him/her to locate the best trade-offs between different competing design alternatives. By utilizing interactive multiobjective optimization in the design process, the designer is able to learn about the problem and about the interdependences between the conflicting design criteria. In addition, (s)he can concentrate only on those compromises that are of interest to him/her.
In our approach, novel aspects to wastewater treatment plant design are the consideration of multiple evaluation criteria and interactive nature of the design process. So far, we have found only one paper in this field that deals with multiple objectives and there the idea is to produce an approximation of all the compromise solutions to the multiobjective optimization problem considered. When compared to this approach, our interactive approach is more computationally efficient because we do not try to approximate all the compromise solutions of which many can be uninteresting to the designer. To our knowledge, there are no papers on utilizing interactive multiobjective optimization in wastewater treatment plant design which makes this kind of approach an entirely novel in wastewater treatment plant design, although such interactive tools are succesfully utilized in other fields.
We have conducted a preliminary study on combining an interactive multiobjective optimization tool IND-NIMBUS (http://ind-nimbus.it.jyu.fi/) with the GPS-X simulator (http://www.hydromantis.com/software02.html) designed for simulating wastewater treatment processes. The approach was tested with a case study of wastewater treatment plant design following the activated sludge process described above. The case study included three conflicting objectives, namely, the residual ammonium nitrogen concentration, the dose of alkalinity chemical and the consumption of energy by aeration. In this paper, we extend the case study to be more realistic by considering more conflicting objectives. The possibilities of this interactive design strategy are illustrated by reporting results from this case study and analyzing their significance and the potential of this novel point of view.