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The control of operational costs is one of the main goals of resource management problem in cloud computing (CC). This paper presents a new mathematical model based on group technology (GT) to map the virtual machines (VMs) to workflows in order to control some costs (e.g. transfer costs, penalty costs and server cost) when the VMs are running. GT is a well-known manufacturing technique in industrial environments which can control some measures (e.g. part movements, resource utilization). In large size problems a cuckoo optimization algorithm (COA) is proposed. To test the effectiveness of our approaches, we first generate a set of problems randomly and then compare the model and COA with a well-known algorithm in literature called Round robin (RR). Analyzing the computational results proves that our approaches give better performance than RR.

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