A heuristic for inventory management of slow-moving items

Abstract

Abstract. The traditional approach in the study of inventory systems is to give more importance to items whose demands are either large or very difficult to forecast, discounting the importance of inventory items with small demand. The objective of this paper is to present a simple and practical heuristic to the slow-moving items problem. First we provide insight into previous work in this area and also give a brief outline of classical models in stochastic inventory theory. Then we present the proposed approach and detail the heuristic. We summarize the paper with an analysis of the simulation results and finish with the conclusions that are drawn from the results.

Keywords:

• inventory
• control
• slow-moving
• items
• simulation
• heurisitc

Additional information

Notes on contributors

JORGE HADDOCK

JORGE HADDOCK is an associate professor of Industrial Engineering and Operations Research in the Department of Decision Sciences and Engineering Systems at Rensselaer Polytechnic Institute. He holds a BSCE from the University of Puerto Rico, a MSMgtE from Rensselaer, and a PhD in Industrial Engineering from Purdue University. Professor Haddock's primary teaching interests include operations research and production planning and inventory control courses at the undergraduate and graduate levels. His primary research interests involve modelling of manufacturing/production and inventory control systems, as well as the design and implementation of simulation modelling and analysis tools. He has authored or co-authored over 70 technical publications and reports. His research has been funded by the US and New York State Governments (NSF, NASA, UMTA), Alcoa, GM, GE, Kodak, and RCA. Professor Haddock has also been a consultant to several companies including Baxter-Travenol, Citicorp (San Juan), Citibank (Wall Street), Michelin, Bendix and Jiffy Lube. He is a member of Tau Beta Pi, HE, ORSA, TIMS, SCS and the National Academy of Engineering of Mexico. He received the prestigious Outstanding Young Industrial Engineer Award from HE in 1990 and the Martin Luther King, Jr. Faculty/Staff Award at Rensselaer in 1992.

NATARAJAN T. IYER

NATARAJAN IYER currently works as a systems consultant with Oracle Corporation. He received his master's degree in industrial and management engineering from Rensselaer Polytechnic Institute, Troy, New York and his bachelor's degree in mining engineering from the Indian Institute of Technology, Kharagpur, India. He is a member of the Houston chapter of the Institute of Industrial Engineers.

AMIT NAGAR

AMIT NAGAR is a PhD candidate in the Decision Sciences and Engineering Systems department at Rensselaer Polytechnic Institute. He holds a master's degree in operations research from University of Delhi, India. His current research interests include production planning and scheduling, and application of global optimization techniques, such as genetic algorithms to scheduling problems.