As global concerns over sustainability grow, integrating advanced mathematical optimization techniques into decision support systems is vital for sustainable supply chain management. Modern supply chains are intricate networks that balance economic, environmental, and social dimensions to meet business and societal demands. Achieving sustainability while ensuring profitability and efficiency necessitates robust, data-driven strategies. Multi-criteria decision-making methods and AI-driven approaches are essential for navigating trade-offs between objectives like cost reduction and environmental impact. Emphasizing circular economy models and carbon footprint reduction highlights the need for innovative optimization solutions. To meet international sustainability standards, such as the UN Sustainable Development Goals, organizations must develop decision support systems that guide strategic planning and operational improvements sustainably.

This Research Topic aims to showcase advancements in mathematical optimization and decision support systems for sustainable supply chain management, fostering interdisciplinary research that addresses global sustainability imperatives. Submissions are welcome on both theoretical advancements and practical implementations, particularly those aligned with multi-objective approaches targeting economic, environmental, and social sustainability.

Key themes include:
- Multi-objective optimization for sustainability in supply chains
- AI-enhanced decision support systems
- Optimization in circular economy and closed-loop supply chains
- Life cycle sustainability assessment
- Carbon footprint reduction and green logistics
- Advanced inventory management and waste reduction
- Decision support for corporate social responsibility (CSR)
- Resilience and adaptability through predictive analytics

Contributors are invited to submit original research articles, comprehensive reviews, and case studies that provide insights into how mathematical optimization can promote sustainable practices across supply chains. Authors are encouraged to bridge theoretical models with real-world applications and incorporate methodologies from engineering, management science, and environmental studies to contribute to global sustainability.

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Mathematical Optimization for Decision Support Systems: Practices and Strategies for Sustainable Supply Chain Management