Optimal Inventory Control and Management Techniques

Optimal Inventory Control and Management Techniques

Mandeep Mittal (Amity School of Engineering and Technology, India) and Nita H. Shah (Gujarat University, India)
Release Date: March, 2016|Copyright: © 2016 |Pages: 406
ISBN13: 9781466698888|ISBN10: 1466698888|EISBN13: 9781466698895|DOI: 10.4018/978-1-4666-9888-8


Stock management and control is a critical element to the success and overall financial well-being of an organization. Through the application of innovative practices and technology, businesses are now able to effectively monitor their operations and manage their inventory by evaluating sales patterns and customer preferences.

Optimal Inventory Control and Management Techniques explores emergent research in stock management and product control within organizations. Featuring diverse perspectives on the implementation of various optimization techniques, genetic algorithms, and datamining concepts, as well as research on big data applications for inventory management, this publication is a comprehensive reference source for practitioners, educators, and researchers in the fields of logistics, operations management, and retail management.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Big Data
  • Customer behavior
  • Deteriorating Inventory
  • Logistics
  • Optimal Ordering
  • Queuing Networks
  • System Modeling

Reviews and Testimonials

Mathematicians and computer scientists offer diverse perspectives on implementing various optimization techniques, genetic algorithms, and data mining concepts for controlling and managing the inventory of a business. Their topics include a lot size model for reverse logistics with quadratic demand, a deteriorating inventory model under permissible delay in payments and fuzzy environment, modeling an inventory system with variable demands and lead times using a fuzzy approach, optimal inventory classification using data mining techniques, and a gentle introduction to the Bayesian paradigm for some inventory models.

– ProtoView Reviews

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Mandeep Mittal is an Assistant Professor in the Department of Computer Science and Dean (Student’s Activities) at Amity School of Engineering and Technology, New Delhi, India. He has completed his Ph.D. (Inventory Control and Management) from University of Delhi and M.Sc. (Applied Mathematics) from IIT Roorkee, India. He has published a number of research papers in International Journals including Applied Mathematics and Computation, Int. Journal of Systems and Science, Int. Journal of Inventory Control and Management, Int. Journal of Applied Industrial Engineering, Int. Journal of Industrial Engineering Computations, Int. Journal of Strategic Decision Sciences, Int. Journal of Services Operations and Informatics and Int. Journal Revista Invetigacion Operacional. He is a member of editorial board, Int. Journals Revista Invetigacion Operacional and Int. Journal of Control and Systems Engineering.
Nita H. Shah is a professor in the Department of Mathematics, Gujarat University, Ahmedabad, India. She received her Ph.D. in inventory control management, operations research. Currently, she is engaged in research in inventory control and management, supply chain management, forecasting and information technology and information systems, neural networks, sensors and image processing. She has more than 275 papers published in international and national journals. She is author of four books. She is serving as a member of the editorial board of Investigation Operational, Journal of Social Science and Management, International Journal of Industrial Engineering and Computations and Mathematics Today.