A Demand Forecasting Methodology for Fuzzy Environments


Kabak O., Uelengin F.

JOURNAL OF UNIVERSAL COMPUTER SCIENCE, vol.16, no.1, pp.121-139, 2010 (Journal Indexed in SCI) identifier

  • Publication Type: Article / Article
  • Volume: 16 Issue: 1
  • Publication Date: 2010
  • Title of Journal : JOURNAL OF UNIVERSAL COMPUTER SCIENCE
  • Page Numbers: pp.121-139

Abstract

Several supply chain and production planning models in the literature assume the demands are fuzzy but most of them do not offer a specific technique to derive the fuzzy demands. In this study, we propose a methodology to obtain a fuzzy-demand forecast that is represented by a possibilistic distribution. The fuzzy-demand forecast is found by aggregating forecasts based on different sources; namely statistical forecasting methods and experts' judgments. In the methodology, initially, the forecast derived from the statistical forecasting techniques and experts' judgments are represented by triangular possibilistic distributions. Subsequently, those results are combined by using weights assigned to each of them. A new objective weighting approach is used to find the weights. The proposed methodology is illustrated by an example and a sensitivity analysis is provided.