Sustainable Production and Logistics : Modeling and Analysis book cover
1st Edition

Sustainable Production and Logistics
Modeling and Analysis

  • Available for pre-order. Item will ship after March 8, 2021
ISBN 9780367431303
March 8, 2021 Forthcoming by CRC Press
352 Pages 81 B/W Illustrations

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Book Description

Sustainable Production and Logistics: Modeling and Analysis

Subject Guide: Engineering - Industrial & Manufacturing


This book presents issues faced by planners of production and distribution operations in terms of smart manufacturing and sustainability, using efficient quantitative techniques in a variety of decision-making situations.

Addressing the state-of-the-art of the smart and sustainable sides of production and distribution planning operations, it highlights how a current issue can be effectively approached and what particular quantitative technique can be used. The book goes on to provide a foundation in the new and fast-growing digital journey, and includes logistics 4.0 inside Industry 4.0, along with case studies.

The information in this book is useful worldwide, especially in Europe, Turkey, and Japan. It is written for academicians, researchers, practitioners, and students.

Table of Contents

1. Mitigating Customer Initiated Warranty Fraud for Remanufactured Products in Reverse Supply Chain. 2. Price Decision for New and Remanufactured High-Technology Products under Vertical Nash Model. 3. Disassembly Line Balancing of an End-of-life Product: A Case of Wind Turbine. 4. A Differential Evolution Algorithm for Balancing Mixed-model Disassembly Lines. 5. Integrated Collection-Disassembly-Distribution Problem. 6. Trade-in-to-Upgrade Policymaking in a Digital Twin Disassembly-to-Order System for the Consumer Electronics Industry. 7. Use of Metaheuristics in Reverse Logistics and De-Manufacturing. 8. Reverse Logistics Network Design for Recycling of Packaging Waste: A Case Study. 9. Comparison of Sensor-Embedded Closed-Loop Supply Chain Systems with Regular Systems. 10. DEMATEL-Based Analysis of the Factors Hindering the Effective Use of Industry 4.0 Technologies in Reverse Logistics. 11. Considering Service Level for Planning of Forward/Reverse Supply Chain Network Under Uncertainties. 12. Two-Stage Repair-Full Refund Warranty Policy Analysis for Remanufactured Products in Reverse Supply Chain. 13. An Application of Warehouse Layout and Order Picking in a Distribution Centre. 14. Application of Analytical Network Process Based BOCR Model on Green Supplier Selection Problem: A Case of ISO 14001 Certified Hotel. 15. A Group Decision Making Approach Using Fuzzy AHP and Fuzzy VIKOR for Green Supplier Evaluation. 16. An Improved Extension of Weighted Hierarchical Fuzzy Axiomatic Design: Sustainable Route Selection Problem in Intermodal Transportation Networks. 17. Minimizing Delays on Single Line Train Scheduling. 18. Sustainable Scheduling and an Application in Aviation Industry. Index.

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Eren Özceylan, Ph.D., is an Associate Professor of Industrial Engineering Department at Gaziantep University in Turkey. Dr. Özceylan holds BE and MS degrees with first honors from the Industrial Engineering Department of Selçuk University and a PhD degree in Computer Engineering from the Selçuk University, Konya, Turkey. He also had an academic experience as a postdoctoral fellow at Northeastern University in Boston. His research interests are in the areas of sustainable production and distribution planning operations including reverse logistics, closed-loop supply chains and disassembly line balancing. He is also studying in geographic information system-based multi-criteria decision making problems. Dr. Özceylan holds "Science Academy Young Scientific Researchers Award" (BAGEP 2016) and "Young Scientist Award" given by Gaziantep University (2017). Dr. Özceylan is the author of numerous journal and conference papers, the recipient of several research grants within his scholarly areas, and has presented his work at various national and international conferences. Dr. Özceylan is also one of the members of the Turkish Operational Research Society and INFORMS.

Surendra M. Gupta, Ph.D., is a Professor of Mechanical and Industrial Engineering and the Director of the Laboratory for Responsible Manufacturing at Northeastern University in Boston, Massachusetts, USA. He received his BE in Electronics Engineering from Birla Institute of Technology and Science, MBA from Bryant University, and MSIE and Ph.D. in Industrial Engineering from Purdue University. He is a registered professional engineer in the State of Massachusetts, USA. Dr. Gupta’s research interests span the areas of Production/Manufacturing Systems and Operations Research. He is mostly interested in Environmentally Conscious Manufacturing, Reverse and Closed-Loop Supply Chains, Disassembly Modeling and Remanufacturing. He has authored or coauthored twelve books and over 600 technical papers published in edited books, journals and international conference proceedings. His publications have received over 14,300 citations (with an h-index of 61) from researchers all over the world in journals, proceedings, books, and dissertations. He has traveled to all seven continents viz., Africa, Antarctica, Asia, Australia, Europe, North America and South America and presented his work at international conferences on six continents. In addition, he has delivered keynote speeches in international conferences in several countries including Spain, The Netherlands, Denmark, France, Japan, Korea, Thailand, India, Taiwan, China, Saudi Arabia and Turkey. Dr. Gupta has taught over 150 courses in such areas as operations research, inventory theory, queuing theory, engineering economy, supply chain management, and production planning and control. Among the many recognitions received, he is the recipient of outstanding research award and outstanding industrial engineering professor award (in recognition of teaching excellence) from Northeastern University, a distinguished professor award from IEOM Society International and an outstanding doctoral dissertation advisor award from American Society for Engineering Management.