Comparison of Neural Network-Based Forecasting Methods Using Multi-Criteria Decision-Making Tools

Because of today's strong competition, most manufacturing organizations continually try to increase their profits and reduce their costs. Accurate sales forecasting is certainly an inexpensive way to meet these goals because it leads to improved customer service, reduced lost sales and product returns, and more efficient production planning (Doganis et al., 2006). Forecasting future demand is central to the planning and operation of retail business at the macro and micro levels. At the organizational level, forecasts of sales are essential inputs to many decision activities in various functional areas such as marketing, sales, production/ purchasing, as well as finance and accounting (Mentzer & Bienstock, 1998). Sales forecasts also provide a basis for regional and national distribution and replenishment plans. The importance of accurate sales forecasts for efficient inventory management has long been recognized. In addition, accurate forecasts of retail sales can help improve retail supply chain operations, especially for larger retailers who have a significant market share. For profitable retail operations, accurate demand forecasting is crucial in organizing and planning purchasing, production, transportation, and labor force, as well as after-sales services (Zhang, 2009).