Abstract
Sales forecasting is one of the most crucial issues addressed in business. Control and evaluation of future sales still seem concerned both researchers and policy makers and managers of companies. this research propose an intelligent hybrid sales forecasting system Delphi-FCBPN sales forecast based on Delphi Method, fuzzy clustering and Back-propagation (BP) Neural Networks with adaptive learning rate. The proposed model is constructed to integrate expert judgments, using Delphi method, in enhancing the model of FCBPN. Winter’s Exponential Smoothing method will be utilized to take the trend effect into consideration. The data for this search come from an industrial company that manufactures packaging. Analyze of results show that the proposed model outperforms other three different forecasting models in MAPE and RMSE measures.
Highlights
INTRODUCTIONTo strengthen the competitive advantage in a constantly changing environment, the manager of a company must make the right decision in the right time based on thein formation at hand
Sales forecasting plays a very important role in business strategy
As hybrid intelligent systems can solve non-linear prediction, this article proposes an integration of a hybrid system FCBPN within an architecture of Enterprise Resource Planning (ERP) to improve and extend the management sales module to provide sales forecasts and meet the needs of decision makers of the company
Summary
To strengthen the competitive advantage in a constantly changing environment, the manager of a company must make the right decision in the right time based on thein formation at hand. Obtaining effective sales forecasts in advance can help decision makers to calculate production and material costs, determine the sales price, strategic Operations Management, etc. As hybrid intelligent systems can solve non-linear prediction, this article proposes an integration of a hybrid system FCBPN within an architecture of ERP to improve and extend the management sales module to provide sales forecasts and meet the needs of decision makers of the company. The remainder of the article is constructed as follows: Section 2 is the literature review.
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