A novel approach to safety stock management in a coordinated supply chain with controllable lead time using present value. (15th July 2015)

• Record Type: Journal Article
• Authors: Braglia, Marcello; Castellano, Davide; Frosolini, Marco
• Is Part Of: Applied stochastic models in business and industry. Volume 32:Number 1(2016:Jan./Feb.)
• Page Start: 99
• Page End: 112
• Publication Date: 2015-07-15
• Subjects: present value -- JELS -- inventory -- controllable lead time -- approximation -- safety stock; Stochastic analysis -- Periodicals; Stochastic processes -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Industrial management -- Mathematical models -- Periodicals; 338.00151923
• DOI: 10.1002/asmb.2126
• Languages: English
• ISSNs: 1524-1904

Abstract

Abstract : This paper considers the management of safety stock in a coordinated single‐vendor single‐buyer supply chain under continuous review and Gaussian lead‐time demand. The lead time is supposed controllable, and shortages are not allowed. We follow the present value criterion by considering both inflation and time value of money. Our aim is to present a novel approach to optimizing the safety stock in such system. Under the conditions considered, the safety stock is typically determined according to the value assigned to the safety factor, which is thus treated as a parameter of the model, and not as a decision variable. In this paper, we take a different perspective by putting the order quantity and the safety factor in functional dependence through the adoption of a specific parameter. More precisely, we express the service level as a function of the number of admissible stockouts per time unit and the order quantity. This allows optimizing the safety stock taking into account the constraint on the number of admissible stockouts per time unit. We present both exact and approximated minimization algorithms. Numerical examples are finally shown to illustrate the effectiveness of the approximation algorithm, and to investigate the sensitivity of the model with respect to variations in some fundamental parameters. Copyright © 2015 John Wiley & Sons, Ltd.