Fotios Petropoulos

DEng, BEng, Dr

Accepting PhD Students

20112018
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Research Output 2011 2018

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Article
2018

Another look at forecast selection and combination: evidence from forecast pooling

Kourentzes, N., Barrow, D. & Petropoulos, F., 18 May 2018, In : International Journal of Production Economics.

Research output: Contribution to journalArticle

Pooling
Uncertainty
Forecast combination
Decision modeling
Forecast error
2 Citations

Exploring the sources of uncertainty: why does bagging for time series forecasting work?

Petropoulos, F., Hyndman, R. J. & Bergmeir, C., 16 Jul 2018, In : European Journal of Operational Research. 268, 2, p. 545-554

Research output: Contribution to journalArticle

Time Series Forecasting
Bagging
Time series
Exponential Smoothing
Uncertainty
2 Citations

Forecasting for big data: does suboptimality matter?

Nikolopoulos, K. & Petropoulos, F., 1 Oct 2018, In : Computers and Operations Research. 98, p. 322-329

Research output: Contribution to journalArticle

Open Access
File
Forecasting
Pursuit
Fruit
Optimal Parameter
Extrapolation

Judgmental Selection of Forecasting Models

Petropoulos, F., Kourentzes, N., Nikolopoulos, K. & Siemsen, E., May 2018, In : Journal of Operations Management. 60, p. 34-46

Research output: Contribution to journalArticle

Open Access
File
Time series
Agglomeration
Model selection
Experiments
Information criterion
Open Access
File
shipping
Macros
Decision making
Freight transportation
energy

The inventory performance of forecasting methods: evidence from the M3-competition data

Petropoulos, F., Wang, X. & Disney, S. M., 27 Mar 2018, In : International Journal of Forecasting.

Research output: Contribution to journalArticle

2017

A note on upper bounds for forecast-value-added relative to naive forecasts

Goodwin, P., Petropoulos, F. & Hyndman, R. J., Sep 2017, In : Journal of the Operational Research Society. 68, 9, p. 1082-1084

Research output: Contribution to journalArticle

Open Access
File
Value engineering
Costs
Upper bound
Value added
Forecasting method

Forecasting methods tutorial: The Theta Method

Petropoulos, F. & Nikolopoulos, K., 2017, In : Foresight: the International Journal of Applied Forecasting. 45, p. 11-17

Research output: Contribution to journalArticle

13 Citations

Forecasting with Temporal Hierarchies

Athanasopoulos, G., Hyndman, R. J., Kourentzes, N. & Petropoulos, F., 1 Oct 2017, In : European Journal of Operational Research. 262, 1, p. 60-74

Research output: Contribution to journalArticle

Forecast
Forecasting
Uncertainty Modeling
Temporal Aggregation
Time series

Old dog, new tricks: a modelling view of simple moving averages

Svetunkov, I. & Petropoulos, F., 29 Sep 2017, In : International Journal of Production Research. 14 p.

Research output: Contribution to journalArticle

Moving average
Dog
Modeling
Forecasting method
Statistical model
2 Citations
Open Access
File
Extrapolation
Forecast error
Performance feedback
Inefficiency
Experiment
2016
4 Citations

Another look at estimators for intermittent demand

Petropoulos, F., Kourentzes, N. & Nikolopoulos, K., Nov 2016, In : International Journal of Production Economics. 181, Part A, p. 154-161

Research output: Contribution to journalArticle

Open Access
File
10 Citations

Do 'big losses' in judgmental adjustments to statistical forecasts affect experts' behaviour

Petropoulos, F., Fildes, R. & Goodwin, P., 16 Mar 2016, In : European Journal of Operational Research. 249, 3, p. 842-852

Research output: Contribution to journalArticle

Open Access
File
Forecast
Adjustment
Forecasting
Pharmaceuticals
Sports
12 Citations

Forecasting with multivariate temporal aggregation: the case of promotional modelling

Kourentzes, N. & Petropoulos, F., Nov 2016, In : International Journal of Production Economics. 181, Part A, p. 145-153

Research output: Contribution to journalArticle

Open Access
File
2 Citations

Models for optimising the theta method and their relationship to state space models

Fioruci, J. A., Pellegrini, T. R., Louzada, F., Petropoulos, F. & Koehler, A. B., Oct 2016, In : International Journal of Forecasting. 32, 4, p. 1151-1161 11 p.

Research output: Contribution to journalArticle

Open Access
File
5 Citations

To select or to combine? The inventory performance of model and expert forecasts

Wang, X. & Petropoulos, F., 2016, In : International Journal of Production Research. 54, 17, p. 5271-5282 12 p.

Research output: Contribution to journalArticle

Open Access
File
2015
5 Citations

Amplifying the learning effect via a Forecasting and Foresight Support System

Spithourakis, G., Petropoulos, F., Nikolopoulos, K. & Assimakopoulos, V., 2015, In : International Journal of Forecasting. 31, 1, p. 20-32 13 p.

Research output: Contribution to journalArticle

Open Access
File
17 Citations

Forecasts combinations for intermittent demand

Petropoulos, F. & Kourentzes, N., 2015, In : Journal of the Operational Research Society. 66, 6, p. 914-924 11 p.

Research output: Contribution to journalArticle

Open Access
File

Improving forecast quality in practice

Fildes, R. & Petropoulos, F., 2015, In : Foresight: the International Journal of Applied Forecasting. 36, p. 5-12

Research output: Contribution to journalArticle

2 Citations

Is there a Golden Rule?

Fildes, R. & Petropoulos, F., 2015, In : Journal of Business Research. 68, 8, p. 1742-1745 4 p.

Research output: Contribution to journalArticle

Open Access
File
4 Citations

Relative performance of methods for forecasting Unique Events

Nikolopoulos, K., Litsa, A., Petropoulos, F., Bougioukos, V. & Khammash, M., 2015, In : Journal of Business Research. 68, 8, p. 1785-1791 7 p.

Research output: Contribution to journalArticle

Open Access
File
13 Citations

Simple versus complex selection rules for forecasting many time series

Fildes, R. & Petropoulos, F., 2015, In : Journal of Business Research. 68, 8, p. 1692-1701 10 p.

Research output: Contribution to journalArticle

Open Access
File
2014
10 Citations

A Systemic View of ADIDA framework

Spithourakis, G., Petropoulos, F., Nikolopoulos, K. & Assimakopoulos, V., 2014, In : IMA Journal of Management Mathematics. 25, 2, p. 125-137 13 p.

Research output: Contribution to journalArticle

Open Access
File
31 Citations

Horses for Courses’ in demand forecasting

Petropoulos, F., Makridakis, S., Assimakopoulos, V. & Nikolopoulos, K., 2014, In : European Journal of Operational Research. 237, 1, p. 152-163 12 p.

Research output: Contribution to journalArticle

Open Access
File
37 Citations

Improving forecasting by estimating time series structural components across multiple frequencies

Kourentzes, N., Petropoulos, F. & Trapero Arenas, J. R., 2014, In : International Journal of Forecasting. 30, 2, p. 291-302 12 p.

Research output: Contribution to journalArticle

Open Access
File

Improving forecasting via multiple temporal aggregation

Petropoulos, F. & Kourentzes, N., 2014, In : Foresight: the International Journal of Applied Forecasting. 34, p. 12-17

Research output: Contribution to journalArticle

2013
11 Citations

Empirical heuristics for improving Intermittent Demand Forecasting

Petropoulos, F., Nikolopoulos, K., Spithourakis, G. & Assimakopoulos, V., 2013, In : Industrial Management and Data Systems. 113, 5, p. 683-696 14 p.

Research output: Contribution to journalArticle

Open Access
File
Cost reduction
Automotive industry
Intermittent demand
Heuristics
Demand forecasting
2011
36 Citations

An Aggregate - Disaggregate Intermittent Demand Approach (ADIDA) to forecasting: an empirical proposition and analysis

Nikolopoulos, K., Syntetos, A., Boylan, J. E., Petropoulos, F. & Assimakopoulos, V., 2011, In : Journal of the Operational Research Society. 62, 3, p. 544-554 11 p.

Research output: Contribution to journalArticle

File

Improving the performance of popular supply chain forecasting techniques

Spithourakis, G., Petropoulos, F., Babai, M. Z., Nikolopoulos, K. & Assimakopoulos, V., 2011, In : Supply Chain Forum. 12, 4, p. 16-25 10 p.

Research output: Contribution to journalArticle