Bi-objective MINLP optimization of an industrial water network via benchmarking

Abstract

This paper presents an approach to water system retrofitting by estimating both the economic and environmental impacts of the water network design using bi-objective optimization. The environmental impact is evaluated via benchmarking. By using benchmarking, the decision maker could obtain insight not only into the environmental impact of a certain design belonging to the Pareto optimal solutions, but also into the competitiveness of the design within a particular production sector. The economic criterion used is the total cost of the water network and involves the freshwater cost, annual investment costs of the storage tank, piping and local treatment unit installation, and wastewater treatment cost. This approach uses a mixed-integer nonlinear programming (MINLP) model that enables water re-use and regeneration re-use in batch and semi-continuous processes. The Pareto front is generated using the Normal-Boundary Intersection (NBI) method. The proposed approach can be used for the separate integration of production sections, but also for joint integration of the sections via temporal decomposition. The proposed approach was applied to an industrial case study in a brewery.