Nowadays, the increase of flow traffic between different nodes in manufacturing and service sectors makes many researchers to work on designing hub networks for transporting the flows in order to optimise transportation and decrease transportation costs. Hence, hub location problems are considered as strategic problems and focusing on all aspects of sustainable development is necessary in such decisions. Therefore, considering environmental aspect of sustainable development with economic objective simultaneously, is one of the most important concerns of decision makers and researchers. Due to such changes observed in attitude of researchers and decision makers, a flow transportation network with economic justification and less environmental impacts could be potentially designed. This research aims to develop a multi-objective mathematical model with multiple allocation and multiple capacity levels to minimise both costs and environmental impacts simultaneously. Capacity levels are used to increase the flexibility of the model for selecting hub nodes. Since this problem is a kind of NP-hard problems, a multi-objective deferential evolution (MODE) algorithm is used to solve generated instances. The performance of the proposed model is then evaluated by analysing the sensitivity of the model in response to variations made in the model parameters.