Design of a Multi-Contaminant Water Allocation Network using Multi-Objective Optimization

Abstract

Abstract The core of this study is the design of Water Allocation Networks (WAN) defined by a superstructure integrating different processes, regeneration units and contaminants. In this work, different optimization frameworks are compared to identify the main elements and criteria to be considered as well as the more robust methodology to solve problems involving multiple contaminants and several regeneration units from a multi-objective perspective. A case study previously analysed by (Feng et al., 2008) and (Boix et al., 2011) and formulated as a Nonlinear Programming (NLP) and Mixed Integer Non-Linear Programming (MINLP) problem, respectively, is treated by minimizing objective functions such as fresh water consumption, the number of network connections and the regenerated water flow rate. The comparison of the obtained results show that the use of binary variables in the MINLP approach leads to a better WAN with less connections thus eliminating low flow rates among the processes although the computation time is longer.