Mehmet Murat FadilogluÖnder Bulut2025-10-062019016763770167-637710.1016/j.orl.2018.12.007https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060349776&doi=10.1016%2Fj.orl.2018.12.007&partnerID=40&md5=8fdff85893b12269e7824b954d60cd45https://gcris.yasar.edu.tr/handle/123456789/9434We provide an extension to the embedded Markov chain approach of Fadiloglu and Bulut (2010) for the analysis of lot-per-lot inventory systems with backorders under rationing. This extension generalizes the method so that it can be used for the analysis under (QR) policy. We introduce a new embedded Markov chain of higher dimensionality that keeps track of the ordering process. We finally provide a recursive procedure to generate the steady-state probabilities from the chain and obtain the steady-state distribution. © 2019 Elsevier B.V. All rights reserved.EnglishBatch Orders, Embedded Markov Chains, Inventory Models, Rationing, Embedded Systems, Inventory Control, Probability Distributions, Batch Orders, Embedded Markov Chain, Inventory Models, Inventory Systems, Rationing, Recursive Procedure, Steady State Probabilities, Steady-state Distributions, Markov ProcessesEmbedded systems, Inventory control, Probability distributions, Batch orders, Embedded Markov chain, Inventory models, Inventory systems, Rationing, Recursive procedure, Steady state probabilities, Steady-state distributions, Markov processesArticle