Sustainable Supply Chain Management - Computational Approaches and Modelling

Sustainable Supply Chain Management: Computational Approaches and Modelling explores the intersection of sustainability and supply chain management, emphasizing the power of computational techniques. The book demonstrates how advanced modelling approaches can address the complex challenges inherent in designing and managing sustainable supply chains. It guides readers through optimizing operations with careful consideration of environmental, social, and economic impacts. By integrating sustainability into decision-making, the book provides actionable insights for both academia and industry. This resource serves as a bridge for those seeking to implement robust, data-driven solutions in the realm of sustainable supply chain management.

Beyond foundational concepts, the book highlights emerging modelling techniques and innovative computational tools that enhance supply chain efficiency while supporting sustainability goals. It examines practical solutions to real-world problems, offering strategies for integrating sustainability into every stage of supply chain operations. Additionally, the book discusses the evolving landscape of supply chain management, presenting current challenges and future opportunities in the pursuit of responsible and resilient business practices.

Product details

• Assisted by: Ali Irfan (Editor), Fariba Goodarzian (Editor), Bathrinath Sankaranarayanan (Editor), Syed Mithun Ali (Editor)
• Publisher: Elsevier
• Languages: English
• Product format: Paperback / Softback
• Release: 01.03.2026
• EAN: 9780443338076
• ISBN: 978-0-443-33807-6
• Weight: 450 g
• Subjects: Guides; BUSINESS & ECONOMICS / Management, TECHNOLOGY & ENGINEERING / Industrial Engineering, TECHNOLOGY & ENGINEERING / Manufacturing, BUSINESS & ECONOMICS / Distribution, Energy technology & engineering, Information visualization, Other manufacturing technologies, information architecture, Management of specific areas, Manufacturing industries, Computing & Information Technology, Management and management techniques, Database design and theory, COMPUTERS / Data Science / Data Visualization, Distribution & warehousing management, Distribution and logistics management, Industrial chemistry and manufacturing technologies