Computational Intelligence Techniques for Sustainable Supply Chain Management presents state-of-the-art computational intelligence techniques and applications for supply chain sustainability issues and logistic problems, filling the gap between general textbooks on sustainable supply chain management and more specialized literature dealing with methods for computational intelligence techniques. This book focuses on addressing problems in advanced topics in the sustainable supply chain and will appeal to practitioners, managers, researchers, students, and professionals interested in sustainable logistics, procurement, manufacturing, inventory and production management, scheduling, transportation, and supply chain network design.

Serves as a reference on computational intelligence-enabled sustainable supply chains for graduate students in computer/data science, industrial engineering, industrial ecology, and business
Explores key topics in sustainable supply chain informatics, that is, heuristics, metaheuristics, robotics, simulation, machine learning, big data analytics and artificial intelligence
Provides a foundation for industry leaders and professionals to understand recent and cutting-edge methodologies and technologies in the domain of sustainable supply chain powered by computational intelligence techniques

Table of Contents:

1. A review of computational tools, techniques, and methods for sustainable supply chains
2. Big Data Analytics in Construction: Laying the Groundwork for Improved Project Outcomes
3. Role of UAVs in Sustainable Supply Chain: Queuing theory and Ant Colony Optimization Approach
4. Applying Machine Learning to investigate the enablers of Sustainable Supply Chain Management
5. Scenario Analysis for Long-term Planning: Stratified Decision-Making Models in Sustainable Supply Chains
6. Machine Learning Techniques for Sustainable Industrial Process Control
7. Intelligent Sustainable Infrastructure for procurement and distribution
8. Machine Learning Techniques for Route Optimizations and Logistics Management Description
9. Improving Sustainable Supply Chain through Robotics
10. Computational techniques for green procurement and production
11. Predictive big data analytics for supply chain demand forecasting
12. Bayesian Network Based on Cross Bow-tie to Analyze Differential Effects of Internal and External Risks on Sustainable Supply Chain
13. Optimizing Supply Chain Operations through Digitalization and Customer-centric Strategies: A Case Study of Bigbasket.com
14. Applications of Artificial Intelligence in Echo Global Logistics