TY - JOUR
T1 - Exact analysis of (R, s, S) inventory control systems with lost sales and zero lead time
AU - Esmaili, Nazanin
AU - Norman, Bryan A.
AU - Rajgopal, Jayant
N1 - Publisher Copyright:
© 2019 Wiley Periodicals, Inc.
PY - 2019/3
Y1 - 2019/3
N2 - We study an (R, s, S) inventory control policy with stochastic demand, lost sales, zero lead-time and a target service level to be satisfied. The system is modeled as a discrete time Markov chain for which we present a novel approach to derive exact closed-form solutions for the limiting distribution of the on-hand inventory level at the end of a review period, given the reorder level (s) and order-up-to level (S). We then establish a relationship between the limiting distributions for adjacent values of the reorder point that is used in an efficient recursive algorithm to determine the optimal parameter values of the (R, s, S) replenishment policy. The algorithm is easy to implement and entails less effort than solving the steady-state equations for the corresponding Markov model. Point-of-use hospital inventory systems share the essential characteristics of the inventory system we model, and a case study using real data from such a system shows that with our approach, optimal policies with significant savings in inventory management effort are easily obtained for a large family of items.
AB - We study an (R, s, S) inventory control policy with stochastic demand, lost sales, zero lead-time and a target service level to be satisfied. The system is modeled as a discrete time Markov chain for which we present a novel approach to derive exact closed-form solutions for the limiting distribution of the on-hand inventory level at the end of a review period, given the reorder level (s) and order-up-to level (S). We then establish a relationship between the limiting distributions for adjacent values of the reorder point that is used in an efficient recursive algorithm to determine the optimal parameter values of the (R, s, S) replenishment policy. The algorithm is easy to implement and entails less effort than solving the steady-state equations for the corresponding Markov model. Point-of-use hospital inventory systems share the essential characteristics of the inventory system we model, and a case study using real data from such a system shows that with our approach, optimal policies with significant savings in inventory management effort are easily obtained for a large family of items.
KW - (R, s, S) inventory control policy
KW - discrete time Markov chains
KW - lost sales
UR - http://www.scopus.com/inward/record.url?scp=85062722583&partnerID=8YFLogxK
U2 - 10.1002/nav.21833
DO - 10.1002/nav.21833
M3 - Article
AN - SCOPUS:85062722583
SN - 0894-069X
VL - 66
SP - 123
EP - 132
JO - Naval Research Logistics
JF - Naval Research Logistics
IS - 2
ER -