Abstract
One of the most challenging tasks in managing a supply chain is to select an efficient inventory ordering policy, i.e., deciding on ‘when to order’ and ‘how much to order’ while minimizing the total cost and maximizing the service level. Classical inventory policies based on periodic and continuous-review are generally implemented in practice. In our work, we attempt to combine the characteristics of both periodic-review order-up-to (R, S) policy and continuous-review (s, Q)/(s, S) policies to propose two new hybrid ordering policies, namely continuous-review (s, Q*) and continuous-review (\({s,\mathrm{O}\mathrm{Q}}^{*})\) hybrid policies. We further develop mixed integer linear programming (MILP) models to obtain the optimal policy parameters by considering a single-stage and two-stage supply chain with discrete, deterministic demand over a finite planning horizon. The proposed policies are benchmarked against the existing order policies, namely (R, S), (s, Q), (s, S) and hybrid (R, S, Qmin) policies. From results, we observe that the performance of the proposed hybrid policies outperforms the existing classical and hybrid policies in terms of total supply chain cost.
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Acknowledgements
The support from Alexander von Humboldt Foundation and the University of Passau is gratefully acknowledged. The authors are grateful to the reviewers and editors for their valuable feedback that have helped us improve the earlier version of the work.
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Santhanam, B., Sethupathi, P.V.R., Rajendran, C., Ziegler, H. (2021). A Comparative Study on Classical and New Hybrid Continuous-Review Inventory Ordering Policies in a Supply Chain Using Mathematical Models. In: Vipin, B., Rajendran, C., Janakiraman, G., Philip, D. (eds) Emerging Frontiers in Operations and Supply Chain Management. Asset Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-16-2774-3_1
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DOI: https://doi.org/10.1007/978-981-16-2774-3_1
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