Optimization of water networks using bound contraction

Area of Science:

• Chemical Engineering
• Environmental Engineering
• Operations Research

Background:

• Industrial water use leads to significant freshwater consumption and effluent generation.
• Optimizing water reuse networks is crucial for sustainability and cost reduction in manufacturing processes.
• Existing models may not fully account for pretreatment units or complex contaminant scenarios.

Purpose of the Study:

• To develop a mixed-integer nonlinear programming (MINLP) optimization model for industrial water reuse network synthesis.
• To incorporate scenarios with and without pretreatment units into the water network design.
• To minimize freshwater intake, effluent discharge, and overall annual costs.

Main Methods:

• Formulation of a MINLP model with bilinear terms for water reuse network synthesis.
• Implementation of the bound contraction technique to improve optimization efficiency.
• Coding the model in General Algebraic Modeling System (GAMS) for practical application.

Main Results:

• The developed optimization model successfully identified global optimal solutions for water reuse networks.
• The bound contraction technique effectively reduced the search space for optimal solutions.
• Case studies with single and multiple contaminants demonstrated the model's applicability, including pretreatment units.

Conclusions:

• The proposed optimization strategy enables the efficient design and reevaluation of industrial water reuse networks.
• The model contributes to developing more sustainable and cost-effective water management configurations.
• The findings support enhanced water resource management in industrial settings.