This seminar is organised by the Oxford Martin Programme on Complexity, The Institute for New Economic Thinking at the Oxford Martin School and the CABDyN Centre
Speaker: K. Y. Michael Wong, Department of Physics, Hong Kong University of Science and Technology
Abstract: Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimisation of cost functions. In general, these can be complex optimisation problems involving many variables. However, physicists noted that in a network, a node variable (such as the amount of resources of the nodes) is connected to a set of link variables (such as the flow connecting the node), and similarly each link variable is connected to a number of (usually two) node variables. This enables one to break the problem into local components, often arriving at distributive algorithms to solve the problems. Compared with centralised algorithms, distributed algorithms have the advantages of lower computational complexity, and lower communication overhead. Since they have a faster response to local changes of the environment, they are especially useful for networks with evolving conditions. This review will cover message?passing algorithms in applications such as resource allocation, transportation networks, facility location, traffic routing, and stability of power grids.
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