Analytical Inventory Management and Optimization

In this vital resource with discussion of and applicability to various industries, Ali, Rabiu, and Ismail guide readers through the challenging environment of inventory management and enable them to successfully balance the demand and supply of items in stock, a critical task in any field.

The book covers a wide range of topics related to inventory management and optimization. After introducing the key concepts and principles of inventory management, such as inventory analytics, optimization, and models, the authors provide a comprehensive and in-depth understanding of various inventory control techniques that are essential for effective inventory management, such as ABC analysis, EOQ model, safety stock, and reorder point. They then introduce various mathematical models and optimization techniques such as system-level and item-level inventory analysis and show how to perform sensitivity analyses to test the robustness of these models. They then look at the role of inventory management in various industries such as supply chain management and logistics, manufacturing, and more; and address the effects and integration of cutting-edge technologies like artificial intelligence, machine learning, and robotics to conventional inventory management practices. Additional topics include inventory forecasting, inventory management systems, inventory auditing and control, risk management. In combining mathematical underpinnings in the area with practical case studies throughout, readers will gain a solid understanding of the real-world applications of these different techniques so that they can apply inventory management and optimization best practices in their workplace.

The comprehensive coverage makes the book a valuable reference for practitioners and students, particularly postgraduate and MBA students, who require such insights to improve business functions and make informed decisions. Because it provides the foundational mathematical knowledge required to comprehend any chapter, it is also accessible for readers without a strong background in mathematics.

Majid Khan Bin Majahar Ali is a senior lecturer in the School of Mathematical Sciences at Universiti Sains Malaysia, where he joined in 2017 specializing in Operational Research. He earned his Ph.D. in Mathematics from Universiti Malaysia Sabah. His research spans seaweed cultivation, solar drying systems, and the use of big data for models and simulations to predict moisture loss under various environmental conditions.

Sani Rabiu is a lecturer at the Nigerian Defence Academy in Kaduna. He holds a B.Sc. and a Postgraduate Diploma in Education from Bayero University Kano, a Postgraduate Diploma from the Nigerian Defence Academy, an M.Ed. from the National Open University of Nigeria, and an M.Sc. from Aliko Dangote University of Science and Technology. Currently completing his Ph.D. in Applied Mathematics at Universiti Sains Malaysia, his research focuses on mathematical modeling and optimization techniques to address real-world problems.

Mohd Tahir Ismail is an associate professor and researcher at Universiti Sains Malaysia. His research interests include financial time series, econometrics, categorical data analysis, and applied statistics. He is currently the Vice President of the Malaysian Mathematical Sciences Society and an active member of other scientific professional bodies.