Gradient Boosting and Deep Learning Models Approach to Forecasting Promotions Efficiency in FMCG Retail

[1]  Juan R. Trapero,et al.  On the identification of sales forecasting models in the presence of promotions , 2015, J. Oper. Res. Soc..

[2]  Rob Rob Broekmeulen,et al.  Analysis and Forecasting of Demand During Promotions for Perishable Items , 2016 .

[3]  Robert C. Blattberg,et al.  Modelling the Effectiveness and Profitability of Trade Promotions , 1987 .

[4]  R. Fildes,et al.  Use and misuse of information in supply chain forecasting of promotion effects , 2018, International Journal of Forecasting.

[5]  Chetana Hegde,et al.  Sales-forecasting of Retail Stores using Machine Learning Techniques , 2018, 2018 3rd International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS).

[6]  Georgia Perakis,et al.  The Impact of Linear Optimization on Promotion Planning , 2014, Oper. Res..

[7]  Hon-Kwong Lui,et al.  Machine Learning for Direct Marketing Response Models: Bayesian Networks with Evolutionary Programming , 2006, Manag. Sci..

[8]  Cinzia Mortarino,et al.  Regular and promotional sales in new product life cycles: Competition and forecasting , 2019, Comput. Ind. Eng..

[9]  Joanna Henzel,et al.  Gradient Boosting Application in Forecasting of Performance Indicators Values for Measuring the Efficiency of Promotions in FMCG Retail , 2020, 2020 15th Conference on Computer Science and Information Systems (FedCSIS).

[10]  Spyros Makridakis,et al.  The art and science of forecasting An assessment and future directions , 1986 .

[11]  Tianqi Chen,et al.  XGBoost: A Scalable Tree Boosting System , 2016, KDD.

[12]  Fotios Petropoulos,et al.  Forecasting with multivariate temporal aggregation: the case of promotional modelling , 2016 .

[13]  Jan Fransoo,et al.  SKU demand forecasting in the presence of promotions , 2009, Expert Syst. Appl..