Computational Intelligence Techniques for Sustainable Supply Chain Management

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 businessExplores 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 INDICE: 1. A review of computational tools, techniques, and methods for sustainable supply chains2. Big Data Analytics in Construction: Laying the Groundwork for Improved Project Outcomes3. Role of UAVs in Sustainable Supply Chain: Queuing theory and Ant Colony Optimization Approach4. Applying Machine Learning to investigate the enablers of Sustainable Supply Chain Management5. Scenario Analysis for Long-term Planning: Stratified Decision-Making Models in Sustainable Supply Chains6. Machine Learning Techniques for Sustainable Industrial Process Control7. Intelligent Sustainable Infrastructure for procurement and distribution8. Machine Learning Techniques for Route Optimizations and Logistics Management Description9. Improving Sustainable Supply Chain through Robotics10. Computational techniques for green procurement and production11. Predictive big data analytics for supply chain demand forecasting12. Bayesian Network Based on Cross Bow-tie to Analyze Differential Effects of Internal and External Risks on Sustainable Supply Chain13. Optimizing Supply Chain Operations through Digitalization and Customer-centric Strategies: A Case Study of Bigbasket.com14. Applications of Artificial Intelligence in Echo Global Logistics

• ISBN: 978-0-443-18464-2
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 468
• Fecha Publicación: 23/05/2024
• Nº Volúmenes: 1
• Idioma: Inglés