Cost and water footprint trade-off in a supply chain optimization model

Area of Science:

• Environmental science and management
• Operations research
• Industrial ecology

Background:

• Water footprint (WF) quantifies freshwater use in industrial systems.
• Existing literature primarily focuses on product WF assessment, not supply chain decision-making.
• Climate change necessitates adaptive strategies for water-intensive industries.

Purpose of the Study:

• To develop a bi-objective optimization model for supplier selection in supply chains.
• To simultaneously minimize economic costs and water footprint (WF).
• To determine optimal actions for supply shortages considering WF.

Main Methods:

• Development of a bi-objective optimization model for supplier selection.
• Integration of water footprint (WF) into cost minimization objectives.
• Demonstration through three case studies, including a stochastic variant.

Main Results:

• The model effectively minimizes both supply chain costs and water footprint (WF).
• Water footprint of raw materials significantly influences decisions on supply shortages.
• WF becomes a critical factor in optimization when assigned a weight of at least 20-50%, depending on the case.
• Increasing WF weight inversely impacts total cost when WF significance is reached.

Conclusions:

• The developed model provides a robust tool for optimizing supply chains with dual cost and water footprint objectives.
• Integrating WF into supplier selection and shortage management is crucial for sustainable industrial practices.
• The model's findings highlight the importance of considering embedded WF in raw materials for effective climate change adaptation.