Computational Intelligence Techniques for Sustainable Supply Chain Management

Sanjoy Kumar Paul, Sandeep Kautish, Sanjoy Kumar Paul, Sandeep Kautish

• Publisher: Academic Press
• Year: 2024
• Print ISBN:
  9780443184642
• eBook ISBN:
  9780443184659
• Topic: Computer Science
• Subtopic: Business Intelligence
• Index: Computer Science

Sustainable supply chain management involves integrating environmentally and financially viable practices into the complete supply chain lifecycle, from product design and development to material selection and sourcing, manufacturing, packaging, transportation, and distribution. A sustainable supply chain ensures balance between economic, social, and environmental performances – such as better assurance of human rights, ethical work practices, carbon footprint reduction, waste management, and resource efficiency. 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. This book focuses on addressing problems in advanced topics in the sustainable supply chain, and will appeal to practitioners, managers, researchers, academicians, students, and professionals interested in sustainable logistics, sustainable procurement, sustainable manufacturing, sustainable inventory and production management, sustainable scheduling, sustainable transportation, and sustainable 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

• Cover
• Title page
• Table of Contents
• Copyright
• Contents
• List of contributors
• About the editors
• Preface
• Acknowledgments
• List of Illustrations
• List of Tables
• Chapter one : A review of computational tools, techniques, and methods for sustainable supply chains
• Chapter two : Big data analytics in construction: laying the groundwork for improved project outcomes
• Chapter three : Role of unmanned air vehicles in sustainable supply chain: queuing theory and ant colony optimization approach
• Chapter four : Exploring the enablers of sustainable supply chain management: A simplified computational intelligence perspective
• Chapter five : Scenario analysis for long-term planning: stratified decision-making models in sustainable supply chains
• Chapter six : Machine learning techniques for sustainable industrial process control
• Chapter seven : Intelligent sustainable infrastructure for procurement and distribution
• Chapter eight : Machine learning techniques for route optimizations and logistics management description
• Chapter nine : Revolutionizing sustainability: the role of robotics in supply chains
• Chapter ten : Computational techniques for sustainable green procurement and production
• Chapter eleven : Predictive big data analytics for supply chain demand forecasting
• Chapter twelve : Bayesian network based on cross bow-tie to analyze differential effects of internal and external risks on sustainable supply chain
• Chapter thirteen : Streamlining supply chain operations: A case study of bigbasket.com
• Chapter fourteen : Applications of artificial intelligence in Echo Global Logistics
• Index
• A