This paper builds upon the study by Montanari et al. (2015). These authors presented a probabilistic approach, named M.DPA.eoq, to predict the demand seen by an upper-tier echelon (e.g., a distribution centre) of a supply network, serving several lower-tier echelons (e.g., retail stores) operating according to an economic order quantity (EOQ) policy. In this paper, we investigate the case of the economic order interval (EOI) policy and thus formulate the Montanari demand probabilistic approach in the EOI scenario (M.DPA.eoi) framework. Although its analytic formulation is not so simple, the M.DPA.eoi is quite easy to understand and can be implemented without difficulties in general-purpose software, such as Microsoft ExcelTM. Therefore, it is expected to be directly exploited by supply network managers, to estimate the distribution of the demand the upper-tier echelon will face in a defined network structure. The model is tested on four scenarios, with different network structures and different behaviours of the lower-tier echelons.

An analytic model to investigate the demand propagation in EOI supply networks / Montanari, Roberto; Bottani, Eleonora. - In: INTERNATIONAL JOURNAL OF SIMULATION AND PROCESS MODELLING. - ISSN 1740-2131. - 12:2(2017), pp. 124-150. [10.1504/IJSPM.2017.083528]

An analytic model to investigate the demand propagation in EOI supply networks

MONTANARI, Roberto;
2017-01-01

Abstract

This paper builds upon the study by Montanari et al. (2015). These authors presented a probabilistic approach, named M.DPA.eoq, to predict the demand seen by an upper-tier echelon (e.g., a distribution centre) of a supply network, serving several lower-tier echelons (e.g., retail stores) operating according to an economic order quantity (EOQ) policy. In this paper, we investigate the case of the economic order interval (EOI) policy and thus formulate the Montanari demand probabilistic approach in the EOI scenario (M.DPA.eoi) framework. Although its analytic formulation is not so simple, the M.DPA.eoi is quite easy to understand and can be implemented without difficulties in general-purpose software, such as Microsoft ExcelTM. Therefore, it is expected to be directly exploited by supply network managers, to estimate the distribution of the demand the upper-tier echelon will face in a defined network structure. The model is tested on four scenarios, with different network structures and different behaviours of the lower-tier echelons.
2017
supply network; economic order interval; EOI; demand propagation; demand distribution; M.DPA.eoi; bullwhip effect
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14089/106
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