Reorganizing a new generation airline network based on an Ant-Colony Optimization-inspired Small-World network

We describe a real-world application for a next generation airline network using a novel Small-World (SW) network architecture. An emergent method that creates a new type of Small-World network with less average path-length than that obtained with conventional small-world networks is presented. This method is inspired from an Ant-Colony Optimization (ACO) algorithm. The resultant network architecture becomes a multi-star network, which yields a large clustering coefficient and the shortest average path-length among the conventional complex networks such as the Watts-Strogatz and Barabási-Albert models etc., from both a theoretical and an experimental analysis of the properties of those networks. Given the advantageous properties of the multi-star network in real-world applications, it could be used to design a new generation global airline network superseding in terms of efficiency and convienience the current, conventional airline network owing to fewer transits and a shorter cruising distance on average from any starting point to any destination on Earth. This will be beneficial not only both to travelers and airline companies, but will also contribute to the reduction of greenhouse gases such as carbon dioxide (CO₂) in the near future, while enhancing communications and transportation worldwide.