Documents disponibles écrits par cet auteur

An aggregate–disaggregate intermittent demand approach (ADIDA) to forecasting / Nikolopoulos, K. in Journal of the operational research society (JORS), Vol. 62 N° 3 Special issue (Mars 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 3 Special issue (Mars 2011) . - pp. 544–554 Titre : An aggregate–disaggregate intermittent demand approach (ADIDA) to forecasting : an empirical proposition and analysis Type de document : texte imprimé Auteurs : Nikolopoulos, K., Auteur ; Syntetos, A. A., Auteur ; Boylan, J. E., Auteur Année de publication : 2011 Article en page(s) : pp. 544–554 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Demand  forecasting  Inventory  management  Intermittent  demand  Aggregation  Empirical  investigation Index. décimale : 001.424 Résumé : Intermittent demand patterns are characterised by infrequent demand arrivals coupled with variable demand sizes. Such patterns prevail in many industrial applications, including IT, automotive, aerospace and military. An intuitively appealing strategy to deal with such patterns from a forecasting perspective is to aggregate demand in lower-frequency ‘time buckets’ thereby reducing the presence of zero observations. However, such aggregation may result in losing useful information, as the frequency of observations is reduced. In this paper, we explore the effects of aggregation by investigating 5000 stock keeping units from the Royal Air Force (UK). We are also concerned with the empirical determination of an optimum aggregation level as well as the effects of aggregating demand in time buckets that equal the lead-time length (plus review period). This part of the analysis is of direct relevance to a (periodic) inventory management setting where such cumulative lead-time demand estimates are required. Our study allows insights to be gained into the value of aggregation in an intermittent demand context. The paper concludes with an agenda for further research. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n3/abs/jors201032a.html [article] An aggregate–disaggregate intermittent demand approach (ADIDA) to forecasting : an empirical proposition and analysis [texte imprimé] / Nikolopoulos, K., Auteur ; Syntetos, A. A., Auteur ; Boylan, J. E., Auteur . - 2011 . - pp. 544–554. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 3 Special issue (Mars 2011) . - pp. 544–554 Mots-clés : Demand  forecasting  Inventory  management  Intermittent  demand  Aggregation  Empirical  investigation Index. décimale : 001.424 Résumé : Intermittent demand patterns are characterised by infrequent demand arrivals coupled with variable demand sizes. Such patterns prevail in many industrial applications, including IT, automotive, aerospace and military. An intuitively appealing strategy to deal with such patterns from a forecasting perspective is to aggregate demand in lower-frequency ‘time buckets’ thereby reducing the presence of zero observations. However, such aggregation may result in losing useful information, as the frequency of observations is reduced. In this paper, we explore the effects of aggregation by investigating 5000 stock keeping units from the Royal Air Force (UK). We are also concerned with the empirical determination of an optimum aggregation level as well as the effects of aggregating demand in time buckets that equal the lead-time length (plus review period). This part of the analysis is of direct relevance to a (periodic) inventory management setting where such cumulative lead-time demand estimates are required. Our study allows insights to be gained into the value of aggregation in an intermittent demand context. The paper concludes with an agenda for further research. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n3/abs/jors201032a.html

Feasibility principles for Downstream Demand Inference in supply chains / Ali, M. M. in Journal of the operational research society (JORS), Vol. 62 N° 3 Special issue (Mars 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 3 Special issue (Mars 2011) . - pp. 474–482 Titre : Feasibility principles for Downstream Demand Inference in supply chains Type de document : texte imprimé Auteurs : Ali, M. M., Auteur ; Boylan, J. E., Auteur Année de publication : 2011 Article en page(s) : pp. 474–482 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Bullwhip  effect  ARIMA  modeling  Downstream  demand  inference  Information  sharing  Supply  chain  management Index. décimale : 001.424 Résumé : Many companies are adopting strategies that enable Demand Information Sharing (DIS) between the supply chain links. Recently, a steady stream of research has identified mathematical relationships between demands and orders at any link in the supply chain. Based on these relationships and strict model assumptions, it has been suggested that the upstream member can infer the demand at the downstream member from their orders. If this is so, DIS will be of no value. In this paper, we argue that real-world modelling requires less restrictive assumptions. We present Feasibility Principles to show that it is not possible for an upstream member to accurately infer consumer demand under more realistic model assumptions. Thus, we conclude that DIS has value in supply chains. We then move our focus to the supply chain model assumptions in the papers arguing that there is value in sharing demand information. Using a simulation experiment, we show that the value of sharing demand information in terms of inventory reductions will increase under more realistic supply chain model assumptions. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n3/abs/jors201082a.html [article] Feasibility principles for Downstream Demand Inference in supply chains [texte imprimé] / Ali, M. M., Auteur ; Boylan, J. E., Auteur . - 2011 . - pp. 474–482. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 3 Special issue (Mars 2011) . - pp. 474–482 Mots-clés : Bullwhip  effect  ARIMA  modeling  Downstream  demand  inference  Information  sharing  Supply  chain  management Index. décimale : 001.424 Résumé : Many companies are adopting strategies that enable Demand Information Sharing (DIS) between the supply chain links. Recently, a steady stream of research has identified mathematical relationships between demands and orders at any link in the supply chain. Based on these relationships and strict model assumptions, it has been suggested that the upstream member can infer the demand at the downstream member from their orders. If this is so, DIS will be of no value. In this paper, we argue that real-world modelling requires less restrictive assumptions. We present Feasibility Principles to show that it is not possible for an upstream member to accurately infer consumer demand under more realistic model assumptions. Thus, we conclude that DIS has value in supply chains. We then move our focus to the supply chain model assumptions in the papers arguing that there is value in sharing demand information. Using a simulation experiment, we show that the value of sharing demand information in terms of inventory reductions will increase under more realistic supply chain model assumptions. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n3/abs/jors201082a.html

Judgement and supply chain dynamics / Syntetos, A. A. in Journal of the operational research society (JORS), Vol. 62 N° 6 (Juin 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 6 (Juin 2011) . - pp. 1138–1158 Titre : Judgement and supply chain dynamics Type de document : texte imprimé Auteurs : Syntetos, A. A., Auteur ; Georgantzas, N. C., Auteur ; Boylan, J. E., Auteur Année de publication : 2011 Article en page(s) : pp. 1138–1158 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : System  dynamics  Inventory  forecasting  Human  judgement  Bullwhip Index. décimale : 001.424 Résumé : Forecasting demand at the individual stock-keeping-unit (SKU) level often necessitates the use of statistical methods, such as exponential smoothing. In some organizations, however, statistical forecasts will be subject to judgemental adjustments by managers. Although a number of empirical and ‘laboratory’ studies have been performed in this area, no formal OR modelling has been conducted to offer insights into the impact such adjustments may have on supply chain performance and the potential development of mitigation mechanisms. This is because of the associated dynamic complexity and the situation-specific nature of the problem at hand. In conjunction with appropriate stock control rules, demand forecasts help decide how much to order. It is a common practice that replenishment orders may also be subject to judgemental intervention, adding further to the dynamic system complexity and interdependence. The system dynamics (SD) modelling method can help advance knowledge in this area, where mathematical modelling cannot accommodate the associated complexity. This study, which constitutes part of a UK government funded (EPSRC) project, uses SD models to evaluate the effects of forecasting and ordering adjustments for a wide set of scenarios involving: three different inventory policies; seven different (combinations of) points of intervention; and four different (combinations of) types of judgmental intervention (optimistic and pessimistic). The results enable insights to be gained into the performance of the entire supply chain. An agenda for further research concludes the paper. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n6/abs/jors201056a.html [article] Judgement and supply chain dynamics [texte imprimé] / Syntetos, A. A., Auteur ; Georgantzas, N. C., Auteur ; Boylan, J. E., Auteur . - 2011 . - pp. 1138–1158. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 6 (Juin 2011) . - pp. 1138–1158 Mots-clés : System  dynamics  Inventory  forecasting  Human  judgement  Bullwhip Index. décimale : 001.424 Résumé : Forecasting demand at the individual stock-keeping-unit (SKU) level often necessitates the use of statistical methods, such as exponential smoothing. In some organizations, however, statistical forecasts will be subject to judgemental adjustments by managers. Although a number of empirical and ‘laboratory’ studies have been performed in this area, no formal OR modelling has been conducted to offer insights into the impact such adjustments may have on supply chain performance and the potential development of mitigation mechanisms. This is because of the associated dynamic complexity and the situation-specific nature of the problem at hand. In conjunction with appropriate stock control rules, demand forecasts help decide how much to order. It is a common practice that replenishment orders may also be subject to judgemental intervention, adding further to the dynamic system complexity and interdependence. The system dynamics (SD) modelling method can help advance knowledge in this area, where mathematical modelling cannot accommodate the associated complexity. This study, which constitutes part of a UK government funded (EPSRC) project, uses SD models to evaluate the effects of forecasting and ordering adjustments for a wide set of scenarios involving: three different inventory policies; seven different (combinations of) points of intervention; and four different (combinations of) types of judgmental intervention (optimistic and pessimistic). The results enable insights to be gained into the performance of the entire supply chain. An agenda for further research concludes the paper. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n6/abs/jors201056a.html