This edited volume is an in-depth collation of the usage of different quantitative decision making techniques in practical areas such as lean & green supply chain, reverse logistics, perishable logistics, closed loop supply chain, sustainable project management, retail management, block chain applications, optimal supplier selection problem, demand/supply modelling, forecasting under uncertainties, scheduling & sequencing, resource constraint logistics, dynamic network supply chain, risk evaluation, and so on. Additionally, the book also solves these issues in theoretical and practical context using innovative mathematical tools. Consisting of selected papers from the 23rd Annual International Conference of the Society of Operations Management, this book's highlight is not only the coverage of interesting topics, but also how these topics are dealt with, such that post-graduate students as well as researchers and industry personnel working in areas like engineering, economics, social sciences, management, mathematics, etc., can derive the maximum benefit by reading or referring to this book. Apart from the emphasis on new mathematical, operations research, operations management, and statistical techniques, the authors also ensure that all the concepts are made clear by highlighting their practical significance in different areas of applications of operations management. By using novel presentation methods, the book offers a good practical flavor of all the different topics relevant to operations management in the coming decades.
Dr. Diptesh Ghosh is a professor in the area of Production and Quantitative Methods Area in Indian Institute of Management (IIM) Ahmedabad. After completing his BTech from Indian Institute of Technology Kharagpur, Dr. Ghosh went on to complete a fellowship (equivalent to PhD) from Indian Institute of Management Calcutta. Prior to his stint at IIM Ahmedabad, Dr. Ghosh taught at IIM Lucknow (India) and University of Groningen (The Netherlands). His core areas of interest are combinatorial optimization, especially in metaheuristics for facility location and layout problems.
Dr. Avijit Khanra is an assistant professor at the Department of Industrial and Management Engineering, Indian Institute of Technology Kanpur. Dr. Khanra has a Bachelor of Engineering degree from Jadavpur University. After working for Tata Motors in their Manufacturing wing, Dr. Khanra obtained his Fellow degree (equivalent to PhD) from IIM Ahmedabad. His areas of research interest are inventory control, supply chain management, production scheduling, and analysis of queues.
Dr. S.V. Vanamalla is an assistant professor at the Department of Industrial and Management Engineering, Indian Institute of Technology Kanpur. Dr. Vanamalla obtained her PhD from the Department of Management Studies, Indian Institute of Science (IISc) after completing her Master of Philosophy in Mathematics from University of Madras. Her areas of research interest are applied operations research, optimization and game theory.
Dr. Faiz Hamid is an assistant professor at the Department of Industrial and Management Engineering, Indian Institute of Technology Kanpur. He has a BTech in Computer Science from West Bengal University of Technology and a Fellowship (equivalent to PhD) from IIM Lucknow. His areas of interest are network optimization, combinatorial optimization, applications of fuzzy logic, data mining, and recommender systems.
Dr. Raghu Nandan Sengupta is professor and Head of Department, Department of Industrial & Management Engineering, Indian Institute of Technology Kanpur. He has a Fellowship from IIM Calcutta. He has attended various fellowship programs and held visiting faculty positions at institutes such as Technische Universität Dresden, Germany, Instituto Superior Técnico (IST) from the University of Lisbon (UTL), Portugal, Informatics and Mechanics University of Warsaw, Poland, Asian Institute of Technology (AIT), Bangkok, Thailand, and Princeton University, USA. His areas of research interest are sequential estimation, statistical and mathematical reliability theory, risk analysis, optimization techniques in finance, and meta heuristic techniques.
