Computational Intelligence Techniques for Sustainable Supply Chain Management 1st Edition

Capture the future of logistics and green operations with Computational Intelligence Techniques for Sustainable Supply Chain Management, 1st Edition by Sanjoy Kumar Paul and Sandeep Kautish. This authoritative volume blends advanced AI methods with real-world sustainability goals to help professionals and researchers transform supply chains for a low-carbon, resilient economy.

Discover how computational intelligence — including neural networks, fuzzy logic, evolutionary algorithms, and swarm optimization — can solve complex supply chain challenges such as demand forecasting, inventory optimization, green procurement, reverse logistics, and carbon-emission minimization. Clear explanations, practical frameworks, and algorithmic strategies make cutting-edge techniques accessible for supply chain managers, data scientists, policy makers, and graduate students.

Packed with case studies and application-driven examples, the book demonstrates measurable outcomes: lower operating costs, improved delivery reliability, reduced environmental impact, and stronger compliance with global sustainability standards. Content is presented with implementation-ready insights applicable across regions — from manufacturing hubs in Asia to retail networks in Europe and distribution systems in North America — making it geopolitically relevant for multinational enterprises and regional supply chains alike.

Whether you’re planning a sustainability roadmap, researching green logistics, or building intelligent decision-support systems, this edition equips you with the tools to design efficient, ethical, and robust supply chains. Enhance your competitive edge and contribute to a sustainable future — add this essential resource to your library today.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.