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An aggregate–disaggregate intermittent demand approach (ADIDA) to forecasting: an empirical proposition and analysis

K Nikolopoulos, A A Syntetos, J E Boylan, F Petropoulos, V Assimakopoulos
2011 Journal of the Operational Research Society  
An Aggregate-Disaggregate Intermittent Demand Approach (ADIDA) to forecasting With respect to temporal aggregation, we must distinguish between overlapping and nonoverlapping cases.  ...  The interaction between temporal and cross-sectional forecasting is also an exciting area of research.  ... 
doi:10.1057/jors.2010.32 fatcat:tj5ueinekzdaxk5b65pbzdj6si

Supply chain forecasting: Theory, practice, their gap and the future

Aris A. Syntetos, Zied Babai, John E. Boylan, Stephan Kolassa, Konstantinos Nikolopoulos
2016 European Journal of Operational Research  
ABSTRACT Supply Chain Forecasting (SCF) goes beyond the operational task of extrapolating demand requirements at one echelon.  ...  It involves complex issues such as supply chain coordination and sharing of information between multiple stakeholders.  ...  , for allowing us to reuse material from the "Hierarchical Forecasting" Guidebook for sub-section 6.2.  ... 
doi:10.1016/j.ejor.2015.11.010 fatcat:duc2wyqkqvfqvaokfm3amz5lbu

A systemic view of the ADIDA framework

G. P. Spithourakis, F. Petropoulos, K. Nikolopoulos, V. Assimakopoulos
2012 IMA Journal of Management Mathematics  
This paper is an attempt to gain mathematical insight into the ADIDA (Aggregate-Disaggregate Intermittent Demand Approach) forecasting framework, by formulating it as a multi-rate signal processing system  ...  Subsequently, theoretical and practical evidence are combined to draw useful conclusions about the framework's performance and make suggestions on its application.  ...  used with non-intermittent demand.  ... 
doi:10.1093/imaman/dps031 fatcat:ixovrxgypzblddnmm5auincwf4

The Wisdom of the Data: Getting the Most Out of Univariate Time Series Forecasting

Fotios Petropoulos, Evangelos Spiliotis
2021 Forecasting  
We describe and discuss approaches that are based on the manipulation of local curvatures (theta method), temporal aggregation, bootstrapping, sub-seasonal and incomplete time series.  ...  We present the concept of the "wisdom of the data" and how data manipulation can result in information extraction which, in turn, translates to improved forecast accuracy by aggregating (combining) forecasts  ...  Acknowledgments: The first author thanks Evelyn and Freddy for their support.  ... 
doi:10.3390/forecast3030029 fatcat:pk2rfozikngxxctmjc44idspga

The Impact of Aggregation Level on Lumpy Demand Management [chapter]

Emilio Bartezzaghi, Matteo Kalchschmidt
2011 Service Parts Management  
Several methods have been proposed to cope with this particular kind of problem and improvements have been proved compared to classical forecasting techniques.  ...  in terms of service and inventory level.  ...  and demand is intermittent).  ... 
doi:10.1007/978-0-85729-039-7_4 fatcat:oh5cavj4yjh4tk3zmabuvhcsga

Non-stationary demand forecasting by cross-sectional aggregation

Bahman Rostami-Tabar, Mohamed Zied Babai, Yves Ducq, Aris Syntetos
2015 International Journal of Production Economics  
In this paper the relative effectiveness of top-down (TD) versus bottom-up (BU) approaches is compared for cross-sectionally forecasting aggregate and sub-aggregate demand.  ...  Valuable insights are offered to demand planners and the paper closes with an agenda for further research in this area. (Bahman ROSTAMI-TABAR), (Aris A.  ...  The problem with the separation of the cross-sectional and temporal dimensions is that the right level of cross-sectional aggregation may vary across time frequencies and vice versa.  ... 
doi:10.1016/j.ijpe.2015.10.001 fatcat:iqrios6mdrcwlhvpa5of5p4t6e

Feature-based intermittent demand forecast combinations: bias, accuracy and inventory implications [article]

Li Li, Yanfei Kang, Fotios Petropoulos, Feng Li
2022 arXiv   pre-print
Intermittent demand forecasting is a ubiquitous and challenging problem in operations and supply chain management.  ...  The proposed framework leads to a significant improvement in forecast accuracy and offers the potential of flexibility and interpretability in inventory control.  ...  GJJ2019163) and the Emerging Interdisciplinary Project of CUFE.  ... 
arXiv:2204.08283v1 fatcat:2eqojy232fdkvo6dajwd5ox4b4

Forecast quality improvement with Action Research: A success story at PharmaCo

Christina Jane Phillips, Konstantinos Nikolopoulos
2018 International Journal of Forecasting  
A successful action research intervention in the Production Planning and Control work unit improved the use and understanding of the forecast function, contributing to substantial saving, enhanced communication  ...  Abstract There is a gap in forecasting research surrounding the theory of integrating and improving forecasting in practice.  ...  Acknowledgements and Funding  ... 
doi:10.1016/j.ijforecast.2018.02.005 fatcat:t557tdnkt5gmxisfwqkdjw7tse

Retail forecasting: Research and practice

Robert Fildes, Shaohui Ma, Stephan Kolassa
2019 International Journal of Forecasting  
Forecasting with temporally aggregated demand signals in a retail supply chain.  ...  sales and potential demand.  ...  For more detail, see Tan and Karabati (2004) who provided a review on the estimation of demand distributions with unobservable lost sales for inventory control.  ... 
doi:10.1016/j.ijforecast.2019.06.004 fatcat:qrrydkizzjg3jmuq7tnpxtlloa

Multi-period portfolio selection with drawdown control

Peter Nystrup, Stephen Boyd, Erik Lindström, Henrik Madsen
2018 Annals of Operations Research  
To illustrate our method's ability to improve forecasts, we compare our method to competitor methods. We include two sets of studies: one with simulated data and one with real data.  ...  In order to produce the weekly demand forecasts, three years of historical weekly factory sales data and weekly wholesaler sales, ending inventory and receipts for the same time period are used.  ...  We discuss the obtained results from the business perspective covering forecasts applications in the inventory optimization and demand planning areas.  ... 
doi:10.1007/s10479-018-2947-3 fatcat:haworusnrfcqvlmkmbidfwb5wu

Forecasting: theory and practice [article]

Fotios Petropoulos, Daniele Apiletti, Vassilios Assimakopoulos, Mohamed Zied Babai, Devon K. Barrow, Souhaib Ben Taieb, Christoph Bergmeir, Ricardo J. Bessa, Jakub Bijak, John E. Boylan, Jethro Browell, Claudio Carnevale (+68 others)
2022 arXiv   pre-print
We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts.  ...  The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges.  ...  Methods for intermittent demand 2.8.1. Parametric methods for intermittent demand forecasting 64 Demand forecasting is the basis for most planning and control activities in any organisation.  ... 
arXiv:2012.03854v4 fatcat:p32c67sy65cfdejq7ndfs3g7dm


Widiyarini Widiyarini
2018 Jurnal Logistik Indonesia  
Through the zero inventory method, company will only produce goods that are needed by the consumers.The number of the work force will increase when the demand is increasing and will lower the work force  ...  A timber factory that produces bare core in the difficulty to deal with the challenge which is caused by the amount of the work forces that are not proportional with the goods which are being produced,  ...  temporal and cross-sectional aggregation and disaggregation methods yang mengkaji metode peramalan permintaan intermiten dan membandingkan beberapa metode perkiraan agregasi dan disaggregasi temporal  ... 
doi:10.31334/jli.v2i2.312 fatcat:uh5zk77qsfedldcvfeqmzgqcnq

25 years of time series forecasting

Jan G. De Gooijer, Rob J. Hyndman
2006 International Journal of Forecasting  
We conclude with comments on possible future research directions in this field.  ...  During this period, over one third of all papers published in these journals concerned time series forecasting.  ...  We also thank two anonymous referees and the editor for many helpful comments and suggestions that resulted in a substantial improvement of this manuscript.  ... 
doi:10.1016/j.ijforecast.2006.01.001 fatcat:o46gaxjojbc6rknhco7ylls5yu

25 Years of IIF Time Series Forecasting: A Selective Review

Jan G. De Gooijer, Rob J. Hyndman
2005 Social Science Research Network  
We conclude with comments on possible future research directions in this field.  ...  We review the past 25 years of time series research that has been published in journals managed by the International Institute of Forecasters (Journal of Forecasting 1982 International Journal of Forecasting  ...  Harvey & Snyder (1990) proposed some continuous-time structural models for use in forecasting lead time demand for inventory control.  ... 
doi:10.2139/ssrn.748904 fatcat:o6ngf2xqf5fu5lqupf3rro6ziq

Developing a common approach for classifying building stock energy models

J. Langevin, J.L. Reyna, S. Ebrahimigharehbaghi, N. Sandberg, P. Fennell, C. Nägeli, J. Laverge, M. Delghust, É. Mata, M. Van Hove, J. Webster, F. Federico (+2 others)
2020 Renewable & Sustainable Energy Reviews  
The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of  ...  The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional  ...  Acknowledgments The authors gratefully acknowledge the strong support of Annex 70 from the International Energy Agency Energy in Buildings and Commu-  ... 
doi:10.1016/j.rser.2020.110276 fatcat:f6z3fu4lbjdvtb3i3s7lmp2mji
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