FUZZY RULE-BASED DEMAND FORECASTING FOR DYNAMIC PRICING

Abstract

In this study, the pricing problem of a transportation service provider company is considered. Our goal is to find optimal prices by using probabilistic dynamic programming. A fuzzy rule-based expert system is used to identify the demand levels under different price levels and other characteristics of the journey. The results obtained by optimal price policies show that the revenue levels and the capacity utilization increase by applying dynamic pricing policy instead of fixed pricing. Thus, the diversification of price policies under different conditions is advantageous for the company.