One of the new issues that have been raised in recent years is the hub network design problem. The hubs are collection and distribution centers that are used for the purpose of less connections and more of indirect than direct communications. They are interface facilities which are used as switch centers to collect and distribute flows in the network. They determine routes and organize traffic between source-destination in order to provide high performance and be more inexpensive. In the hub location problem, the aim is to find a suitable location for the hub and routes for sending information from a source to a destination, in order to reduce costs and gain desired purpose by multiple transfers between the hubs. In this paper, teaching and learning based optimization, particle swarm optimization and imperialist competitive algorithm were studied for locating optimally hubs and allocating nodes to the nearest located hub nodes. Experimental results show that optimal location for hubs by using cluster-based optimization algorithm (TLBO) successfully has been performed with extreme accuracy and precision.

Keywords: Hub Location-allocation, Network, Optimization algorithm, TLBO

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