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Optimization Models for the Continuous Review Inventory System

Optimization Models for the Continuous Review Inventory System

Barry R. Cobb (Department of Marketing, College of Business, Missouri State University, Springfield, MO, USA)
Copyright: © 2017 |Volume: 8 |Issue: 1 |Article: 1 |Pages: 21
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781522513292|DOI: 10.4018/IJORIS.2017010101
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MLA

Cobb, Barry R. "Optimization Models for the Continuous Review Inventory System." IJORIS vol.8, no.1 2017: pp.1-21. http://doi.org/10.4018/IJORIS.2017010101

APA

Cobb, B. R. (2017). Optimization Models for the Continuous Review Inventory System. International Journal of Operations Research and Information Systems (IJORIS), 8(1), 1-21. http://doi.org/10.4018/IJORIS.2017010101

Chicago

Cobb, Barry R. "Optimization Models for the Continuous Review Inventory System," International Journal of Operations Research and Information Systems (IJORIS) 8, no.1: 1-21. http://doi.org/10.4018/IJORIS.2017010101

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Abstract

Businesses that carry inventory as a means of responding to customer demand must decide when to place inventory orders and how much to order. A model for selecting an optimal order quantity and reorder point in the continuous review system is implemented in spreadsheet software. Historical data on period demand and lead time is processed by performing a statistical test to select a mixture distribution for lead time demand. This distribution is incorporated into an expected shortage calculation and cost model where shortages incur lost sales and/or goodwill costs. The lead time demand distribution selection is evaluated through experiments. In examples, employing an incorrect distribution leads to expenditures between one and eighteen percent higher than those experienced with the correct model. A mismatch of the backorder or lost sales model with the correct underlying assumptions leads to expenses between four and thirteen percent larger than necessary in an example problem.

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