In this thesis we investigate dynamic pricing strategies for voice telecommunication industry with economical perspectives considering network resource control as a second priority. The challenge is to propose efficient tools and methods to optimize pricing of the new commercial service. The offer systematically sets a dynamic pricing in real time, depending on time, space and network load. The price offered to the customers typically changes every 30 minutes and differs from an antenna to another one. A simple daily rule is used to compute prices, setting a same price at two different times instants when their network loads are at a same level. The challenge is to optimize pricing for this new offer using an estimation of the traffic and its price sensitivity day by day to accurately compute the prices in a timely fashion.
A deterministic approach has been adopted to estimate demand and load, to formulate the revenue maximization problem and to solve the dynamic pricing problem. Load and demand are modeled as functions of time, cells, and price. Using these given functions several mixed integer quadratic programs (MIQP) have been proposed, studied and solved.