Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 544-554 |
| Number of pages | 11 |
| Journal | Journal of the Operational Research Society |
| Volume | 62 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2011 |
Keywords
- demand forecasting
- inventory management
- intermittent demand
- aggregation
- empirical investigation
Cite this
An Aggregate - Disaggregate Intermittent Demand Approach (ADIDA) to forecasting: an empirical proposition and analysis. / Nikolopoulos, Konstantinos; Syntetos, Aris; Boylan, J E; Petropoulos, Fotios; Assimakopoulos, Vassilios.
In: Journal of the Operational Research Society, Vol. 62, No. 3, 2011, p. 544-554.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An Aggregate - Disaggregate Intermittent Demand Approach (ADIDA) to forecasting:
T2 - an empirical proposition and analysis
AU - Nikolopoulos, Konstantinos
AU - Syntetos, Aris
AU - Boylan, J E
AU - Petropoulos, Fotios
AU - Assimakopoulos, Vassilios
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - demand forecasting
KW - inventory management
KW - intermittent demand
KW - aggregation
KW - empirical investigation
U2 - 10.1057/jors.2010.32
DO - 10.1057/jors.2010.32
M3 - Article
VL - 62
SP - 544
EP - 554
JO - Journal of the Operational Research Society
JF - Journal of the Operational Research Society
SN - 0160-5682
IS - 3
ER -