Abstract
Many important problems in communication networks transportation networks, and logistics networks are solved by the mini mization of cost functions. In general, these can be complex optimizatio problems involving many variables. However, physicists noted that in 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 th node), and similarly each link variable is connected to a number of (usu ally two) node variables. This enables one to break the problem into loca components, often arriving at distributive algorithms to solve the prob lems. Compared with centralized algorithms, distributed algorithms hav the advantages of lower computational complexity, and lower communica tion overhead. Since they have a faster response to local changes of th environment, they are especially useful for networks with evolving condi tions. This review will cover message-passing algorithms in application such as resource allocation, transportation networks, facility location, traffi routing, and stability of power grids. Copyright © 2016 The Institute of Electronics, Information and Communication Engineers.
Original language | English |
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Pages (from-to) | 2237-2246 |
Journal | IEICE Transactions on Communications |
Volume | E99B |
Issue number | 11 |
DOIs | |
Publication status | Published - Nov 2016 |
Citation
Wong, K. Y. M., Saad, D., & Yeung, C. H. (2016). Distributed optimization in transportation and logistics networks. IEICE Transactions on Communications, E99B(11), 2237-2246.Keywords
- Cavity method
- Facility location
- Finite bandwidths
- Message-passing
- Power grids