2026-09-19T18:09:20Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/479022022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Amar Gupta.
Novak, John J. (John Joseph), 1971-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2009-10-01T16:01:16Z
2009-10-01T16:01:16Z
1999
1999
http://hdl.handle.net/1721.1/47902
44021679
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
Includes bibliographical references (p. 68-69).
The military is one of the largest pharmaceutical distributors in the country. In order to minimize the amount of inventory held, and hence warehousing and expired drug costs, data mining techniques can be applied to old transaction records to predict future needs. One powerful method of data mining is the use of neural networks. Neural networks have the ability to learn inventory needs based on past situations which are expected to occur again. Using neural networks to data mine government pharmaceutical supply necessities will enable the reduction of inventory levels as well as improve customer satisfaction by increasing the chance the needed prescriptions will be in stock. This thesis introduces inventory methods, data mining methods, and explores the application of data mining and neural network methods to actual inventory optimization problems. Limits and future direction suggestions are included at the end of the document.
by John J. Novak, Jr.
M.Eng.
69 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Application of neural networks techniques to military pharmaceutical ordering problems
Thesis
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