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.

This book explores recent developments and exciting challenges in operations research and mathematical optimization. It provides the following in a unified and carefully developed presentation: (a) novel problems that have arisen in the real-life optimization domain, highlighting the challenges in each problem; (b) significant methodological advances for solving existing optimization problems, with a special emphasis on large scale problems. The book assumes a decent understanding of matrix algebra, linear and integer programming, non-linear programming, computational complexity, and graph theory. Each chapter in this book starts with an introduction to the underlying optimization technique. It then explores a real-life case study to which the technique will be applied. The objective is to demonstrate how the underlying technique can be utilized to solve a challenging problem. The chapters offer details on how to formulate a research problem into a formal optimization model, reformulate or transform it (if required) to improve computational tractability, and apply necessary customizations to the optimization technique specific to the underlying problem to derive an optimal or near-optimal solution. The book covers various state-of-the-art methods (both exact and heuristics) and modelling approaches in sync with the current research trends, which are still not discussed in typical graduate-level textbooks. Applications covered in the book span the realms of resource planning, telecommunications, scheduling, logistics, education, environmental conservation, and many others. It is thus a valuable resource for post-graduate students of operations research and mathematical optimization. It also serves as a valuable reference for researchers who wish to explore various optimization techniques as part of their research methodologies. The learning from the book should enable the professionals to apply optimization theory and algorithms to their particular field of interest.