IEICE TRANSACTIONS on Communications
Open Access
Distributed Optimization in Transportation and Logistics Networks
-
Full Text Views
38
- Cite this
- Free PDF (1.8MB)
Summary :
Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization 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 centralized 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.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E99-B No.11 pp.2237-2246
- Publication Date
- 2016/11/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2016NEI0003
- Type of Manuscript
- Special Section INVITED PAPER (Special Section on Deepening and Expanding of Information Network Science)
- Category
Authors
K. Y. Michael WONG
the Hong Kong University of Science and Technology
David SAAD
Aston University
Chi Ho YEUNG
Education University of Hong Kong
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
K. Y. Michael WONG, David SAAD, Chi Ho YEUNG, "Distributed Optimization in Transportation and Logistics Networks" in IEICE TRANSACTIONS on Communications,
vol. E99-B, no. 11, pp. 2237-2246, November 2016, doi: 10.1587/transcom.2016NEI0003.
Abstract: Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization 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 centralized 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.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2016NEI0003/_p
Copy
@ARTICLE{e99-b_11_2237,
author={K. Y. Michael WONG, David SAAD, Chi Ho YEUNG, },
journal={IEICE TRANSACTIONS on Communications},
title={Distributed Optimization in Transportation and Logistics Networks},
year={2016},
volume={E99-B},
number={11},
pages={2237-2246},
abstract={Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization 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 centralized 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.},
keywords={},
doi={10.1587/transcom.2016NEI0003},
ISSN={1745-1345},
month={November},}
Copy
TY - JOUR
TI - Distributed Optimization in Transportation and Logistics Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 2237
EP - 2246
AU - K. Y. Michael WONG
AU - David SAAD
AU - Chi Ho YEUNG
PY - 2016
DO - 10.1587/transcom.2016NEI0003
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E99-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 2016
AB - Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization 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 centralized 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.
ER -
English
