Computational Intelligence Techniques for Sustainable Supply Chain Management

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Sanjoy Kumar Paul (Associate Professor, UTS Business School, University of Technology Sydney, Sydney, Australia) Sandeep Kautish, PhD (Professor and Director, Apex Institute of Technology (AIT - CSE), Chandigarh University, Punjab, India)

Computational Intelligence Techniques for Sustainable Supply Chain Management

Sanjoy Kumar Paul (Associate Professor, UTS Business School, University of Technology Sydney, Sydney, Australia), Sandeep Kautish, PhD (Professor and Director, Apex Institute of Technology (AIT - CSE), Chandigarh University, Punjab, India)

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English

Academic Press Inc
03 June 2024

Purchasing & supply management; Operational research; Enterprise software; Artificial intelligence; Expert & knowledge-based systems

Series: Uncertainty, Computational Techniques, and Decision Intelligence

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.

Edited by: Sanjoy Kumar Paul (Associate Professor UTS Business School University of Technology Sydney Sydney Australia), Sandeep Kautish, PhD (Professor and Director, Apex Institute of Technology (AIT - CSE), Chandigarh University, Punjab, India)
Imprint: Academic Press Inc
Country of Publication: United States
Dimensions: Height: 229mm, Width: 152mm,
Weight: 730g
ISBN: 9780443184642
ISBN 10: 044318464X
Series: Uncertainty, Computational Techniques, and Decision Intelligence
Pages: 468
Publication Date: 03 June 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Sanjoy Kumar Paul, PhD is an Associate Professor in operations and supply chain management at the University of Technology Sydney (UTS), Sydney, Australia. He has published more than 140 articles in top-tier journals. He is also an associate editor, area editor, editorial board member, and active reviewer of several reputed journals. Dr. Paul has received several awards, including the ASOR Rising Star Award from the Australian Society for Operations Research, the Excellence in Early Career Research Award from the UTS Business School, and the Stephen Fester Prize for most outstanding thesis from UNSW. Based on his citation records in 2020, 2021 and 2022, he was included in the top 2% of scientists in author databases of standardized citation indicators. His research interests include sustainable supply chain management, supply chain resilience, applied operations research, modeling and simulation, and intelligent decision-making. Sandeep Kautish, PhD is Professor and Director at Apex Institute of Technology (AIT-CSE), Chandigarh University, Punjab India and an academician by choice and has more than 20 years of full-time experience in teaching and research. He has been associated with Asia Pacific University Malaysia for over five years at their TNE site at Kathmandu Nepal in the capacity of Director-Academics. He earned his doctorate degree in Computer Science on Intelligent Systems in Social Networks. He has over 100 publications and his research works have been published in highly reputed journals, i.e., IEEE Transaction of Industrial Informatics, IEEE Access, and Multimedia Tools and Applications, etc. Dr. Kautish has edited 24 books with leading publishers, i.e., Elsevier, Springer, Emerald, and IGI Global, and is an editorial member/reviewer of various reputed journals. His research interests include healthcare analytics, business analytics, machine learning, data mining, and information systems.