Abstract

<p>Currently the operators in the telecommunications market present offers of subscription to the consumers,and given that competition is strong in this area, most of these advertising offers are prepared to attract and / or keep customers.</p><p>For this reason, customers face problems in choosing operators that meet their needs in terms of price, quality of service (QoS), etc..., while taking into account the margin between what is advertising and what is real. Therefore, we are led to solve a problem of decision support. Mathematical modeling of this problem led to the solution of an inverse problem. Specifi-cally, the inverse problem is to find the real Quality of Service (QoS) function knowing the theoretical QoS. To solve this problem we have reformulated in an optimization problem of minimizing the difference between the real quality of service (QoS) and theoretical (QoS). This model will help customers who seek to know the degree of sincerity of Their operators, as well as it is an opportunity for operators who want to maintain their resources so that they gain the trust of customers. The resulting optimization problem is solved using evolutionary algorithms. The numerical results showed the reliability and credibility of our inverse model and the performance and effectiveness of our approach.</p>

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