Islamic Azad Univercity, Qazvin Branch, Department of Industrial Engineering,Qazvin, Iran
Abstract
Nowadays, outsourcing is viewed as a trade strategy and organizations tend to adopt new strategies to achieve competitive advantages in the current world of business. focusing on main copmpetencies, and transferring most of activities to outside resources of organization( outsourcing) is one such strategy is. In this paper, we aim to decide on decision maker agent of transportation system, by applying intelligent agent technology and using learning model which is modeled as a reinforcement learning problem. A Q-learning algorithm is proposed to solve the RL model. Results show that the proposed model given its ability to communicate with environment, adaptability with environment and correcting itself based on learnt data ,the prposed model can be applied as a better and quicker learning model in comparison with other ways of solving of decision making problems.
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