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Author (up) Rojas, F.; Wanke, P.; Coluccio, G.; Vega-Vargas, J.; Huerta-Canepa, G.F. doi  openurl
  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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Author (up) Wanke, P.; Ewbank, H.; Leiva, V.; Rojas, F. pdf  doi
openurl 
  Title Inventory management for new products with triangularly distributed demand and lead-time Type
  Year 2016 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.  
  Volume 69 Issue Pages 97-108  
  Keywords Approximation of functions; Bisection method; Kernel method; Kullback-Leibler divergence; Monte Carlo method; (Q, r) model; R software; Statistical distributions  
  Abstract This paper proposes a computational methodology to deal with the inventory management of new products by using the triangular distribution for both demand per unit time and lead-time. The distribution for demand during lead-time (or lead-time demand) corresponds to the sum of demands per unit time, which is difficult to obtain. We consider the triangular distribution because it is useful when a distribution is unknown due to data unavailability or problems to collect them. We provide an approach to estimate the probability density function of the unknown lead-time demand distribution and use it to establish the suitable inventory model for new products by optimizing the associated costs. We evaluate the performance of the proposed methodology with simulated and real-world demand data. This methodology may be a decision support tool for managers dealing with the measurement of demand uncertainty in new products. (C) 2015 Elsevier Ltd. All rights reserved.  
  Address [Wanke, Peter; Ewbank, Henrique] Univ Fed Rio de Janeiro, COPPEAD Grad Sch Business, BR-21941 Rio De Janeiro, Brazil, Email: victorleivasanchez@gmail.com  
  Corporate Author Thesis  
  Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0305-0548 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000370908300009 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 586  
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Author (up) Wanke, P.; Leiva, V. pdf  doi
openurl 
  Title Exploring the Potential Use of the Birnbaum-Saunders Distribution in Inventory Management Type
  Year 2015 Publication Mathematical Problems In Engineering Abbreviated Journal Math. Probl. Eng.  
  Volume Issue Pages 9 pp  
  Keywords  
  Abstract Choosing the suitable demand distribution during lead-time is an important issue in inventory models. Much research has explored the advantage of following a distributional assumption different from the normality. The Birnbaum-Saunders (BS) distribution is a probabilistic model that has its genesis in engineering but is also being widely applied to other fields including business, industry, and management. We conduct numeric experiments using the R statistical software to assess the adequacy of the BS distribution against the normal and gamma distributions in light of the traditional lot size-reorder point inventory model, known as (Q, r). The BS distribution is well-known to be robust to extreme values; indeed, results indicate that it is a more adequate assumption under higher values of the lead-time demand coefficient of variation, thus outperforming the gamma and the normal assumptions.  
  Address [Wanke, Peter] Univ Fed Rio de Janeiro, COPPEAD Grad Sch Business, BR-21941 Rio De Janeiro, Brazil, Email: victorleivasanchez@gmail.com  
  Corporate Author Thesis  
  Publisher Hindawi Publishing Corp Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1024-123x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000364740300001 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 538  
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