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Abstract Telecommunications industry is a highly competitive one where operators{u2019} strategies usually rely on significantly reducing minute rate in order to acquire more subscribers and thus have higher market share. However, in the last few years, the numbers of customers are noticeably increasing leading to more stress on the network, and higher congestion rate, i.e. worse quality of service (QoS). Because of this, pricing has emerged as a useful tool for simultaneously limiting congestion, and increasing revenue. In this paper a dynamic pricing model is proposed for the mobile calls based on a Monte-Carlo simulation that emulates the processes of calls arrivals, calls durations and the effect of price on both. This model is then integrated with a meta-heuristic evolutionary based optimization algorithm to determine the optimal dynamic pricing schemes according to the call parameters. This integrated framework is a novel approach to dynamic pricing that aims at maximizing revenue and enhancing the QoS |