Resumen

ESCOBAR-GOMEZ, E. N.; DIAZ-NUNEZ, J. J.  y  TARACENA-SANZ, L. F.. Model for Adjustment of Aggregate Forecasts using Fuzzy Logic. Ing. invest. y tecnol. [online]. 2010, vol.11, n.3, pp.289-302. ISSN 2594-0732.

This research suggests a contribution in the implementation of forecasting models. The proposed model is developed with the aim to fit the projection of demand to surroundings of firms, and this is based on three considerations that cause that in many cases the forecasts of the demand are different from reality, such as: 1) one of the problems most difficult to model in the forecasts is the uncertainty related to the information available; 2) the methods traditionally used by firms for the projection of demand mainly are based on past behavior of the market (historical demand); and 3) these methods do not consider in their analysis the factors that are influencing so that the observed behaviour occurs. Therefore, the proposed model is based on the implementation of Fuzzy Logic, integrating the main variables that affect the behavior of market demand, and which are not considered in the classical statistical methods. The model was applied to a bottling of carbonated beverages, and with the adjustment of the projection of demand a more reliable forecast was obtained.

Palabras llave : Production planning; aggregate forecasts; model forecast; demand; fuzzy logic and computational intelligence in industrial engineering.

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