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Author Rojas, F.; Wanke, P.; Coluccio, G.; Vega-Vargas, J.; Huerta-Canepa, G.F.
Title Managing slow-moving item: a zero-inflated truncated normal approach for modeling demand Type
Year 2020 Publication Peerj Computer Science Abbreviated Journal PeerJ Comput. Sci.
Volume 6 Issue Pages 22 pp
Keywords Demand during lead time; Inventory models; Zero-inflated truncated normal statistical distribution
Abstract This paper proposes a slow-moving management method for a system using of intermittent demand per unit time and lead time demand of items in service enterprise inventory models. Our method uses zero-inflated truncated normal statistical distribution, which makes it possible to model intermittent demand per unit time using mixed statistical distribution. We conducted numerical experiments based on an algorithm used to forecast intermittent demand over fixed lead time to show that our proposed distributions improved the performance of the continuous review inventory model with shortages. We evaluated multi-criteria elements (total cost, fill-rate, shortage of quantity per cycle, and the adequacy of the statistical distribution of the lead time demand) for decision analysis using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We confirmed that our method improved the performance of the inventory model in comparison to other commonly used approaches such as simple exponential smoothing and Croston's method. We found an interesting association between the intermittency of demand per unit of time, the square root of this same parameter and reorder point decisions, that could be explained using classical multiple linear regression model. We confirmed that the parameter of variability of the zero-inflated truncated normal statistical distribution used to model intermittent demand was positively related to the decision of reorder points. Our study examined a decision analysis using illustrative example. Our suggested approach is original, valuable, and, in the case of slow-moving item management for service companies, allows for the verification of decision-making using multiple criteria.
Address [Rojas, Fernando] Univ Valparaiso, MicrobioInnovat Ctr, Valparaiso, Chile, Email: fernando.rojas@uv.cl
Corporate Author Thesis
Publisher Peerj Inc Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2376-5992 ISBN Medium
Area Expedition Conference
Notes WOS:000569841300001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1242
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