Can-order policy for the periodic-review joint replenishment problem

Abstract

In this paper we study the stochastic joint replenishment problem. We compare the class of periodic replenishment policies and the class of can-order policies for this problem. We present a method, based on Markov decision theory, to calculate near-optimal can-order policies for a periodic-review inventory system. Our numerical study shows that the can-order policy behaves as well as, if not better than, the periodic replenishment policies. In particular, for examples where the demand is irregular, we find cost differences up to 15% in favour of the can-order policy.

Reducing Costs of Managing Medication Inventory in Automated Dispensing System in Hospital Units

“…Literature on joint replenishment under stochastic demand (SJRP) is applicable in our setting. Johansen and Melchiors [3] noted that in the academic SJRP literature, the continuous review (s,c,S) can-order policy [4] and the periodic replenishment policy [5] received considerable attention. Other policies have been proposed, for example Feng, Wu, Muthuraman and Deshpande [6] introduced a continuous-review (s,c,d,S) policy for managing multi-product inventory with correlated demand.…”

A systematic literature review on the joint replenishment problem solutions: 2006-2015

“…On the stochastic demand models, there are two main replenishment policies: The can-order policy (COP), by Balintfy (1964), in which if any item reaches a must-order point, a replenishment order is made, and if the other items present inventory levels below a can-order point, they are included in the same order (Johansen & Melchiors, 2003;Balintfy, 1964;Khouja & Goyal, 2008). The periodic replenishment policy (PRP), by Atkins & Iyogun (1988), or (T, M) policy, considers a Poisson distributed demand, in which all products follow the same replenishment periodic interval T, and each one is replaced to a pre-determined inventory level M. Later, it has been considered that a set of products would follow the periodic review interval T, while other products that also should be replenished would follow a section of T (Atkins & Iyogun, 1988;Khouja & Goyal, 2008).…”

Constrained Stochastic Joint Replenishment Problem with Option Contracts in Spare Parts Remanufacturing Supply Chain

“…The policy of ordering replenishments delivered multi-variety items to reach a maximum number of inventory positions [16]. Johansen and Melchiors proposed a method of Markov decision theory to resolve a near-optimal result for the periodic inventory problem based on (S, c, s) policies [17]. Kayis et al developed a two-variety-item inventory management model based on semi-Markov decision and proposed a simple enumeration algorithm to solve the problem [18].…”