Fair Optimization and Networks: A Survey
(2014) In Journal of Applied Mathematics- Abstract
- Optimization models related to designing and operating complex systems are mainly focused on some efficiency metrics such as response time, queue length, throughput, and cost. However, in systems which serve many entities there is also a need for respecting fairness: each system entity ought to be provided with an adequate share of the system's services. Still, due to system operations-dependant constraints, fair treatment of the entities does not directly imply that each of them is assigned equal amount of the services. That leads to concepts of fair optimization expressed by the equitable models that represent inequality averse optimization rather than strict inequality minimization; a particular widely applied example of that concept is... (More)
- Optimization models related to designing and operating complex systems are mainly focused on some efficiency metrics such as response time, queue length, throughput, and cost. However, in systems which serve many entities there is also a need for respecting fairness: each system entity ought to be provided with an adequate share of the system's services. Still, due to system operations-dependant constraints, fair treatment of the entities does not directly imply that each of them is assigned equal amount of the services. That leads to concepts of fair optimization expressed by the equitable models that represent inequality averse optimization rather than strict inequality minimization; a particular widely applied example of that concept is the so-called lexicographic maximin optimization (max-min fairness). The fair optimization methodology delivers a variety of techniques to generate fair and efficient solutions. This paper reviews fair optimization models and methods applied to systems that are based on some kind of network of connections and dependencies, especially, fair optimization methods for the location problems and for the resource allocation problems in communication networks. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4796197
- author
- Ogryczak, Wlodzimierz ; Luss, Hanan ; Pioro, Michal LU ; Nace, Dritan and Tomaszewski, Artur
- organization
- publishing date
- 2014
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Applied Mathematics
- article number
- 612018
- publisher
- Hindawi Limited
- external identifiers
-
- wos:000343534100001
- scopus:84907906250
- ISSN
- 1110-757X
- DOI
- 10.1155/2014/612018
- language
- English
- LU publication?
- yes
- id
- aa04402e-7ca6-4b45-9fb0-6042491e3995 (old id 4796197)
- date added to LUP
- 2016-04-01 10:29:35
- date last changed
- 2022-05-17 23:30:50
@article{aa04402e-7ca6-4b45-9fb0-6042491e3995,
abstract = {{Optimization models related to designing and operating complex systems are mainly focused on some efficiency metrics such as response time, queue length, throughput, and cost. However, in systems which serve many entities there is also a need for respecting fairness: each system entity ought to be provided with an adequate share of the system's services. Still, due to system operations-dependant constraints, fair treatment of the entities does not directly imply that each of them is assigned equal amount of the services. That leads to concepts of fair optimization expressed by the equitable models that represent inequality averse optimization rather than strict inequality minimization; a particular widely applied example of that concept is the so-called lexicographic maximin optimization (max-min fairness). The fair optimization methodology delivers a variety of techniques to generate fair and efficient solutions. This paper reviews fair optimization models and methods applied to systems that are based on some kind of network of connections and dependencies, especially, fair optimization methods for the location problems and for the resource allocation problems in communication networks.}},
author = {{Ogryczak, Wlodzimierz and Luss, Hanan and Pioro, Michal and Nace, Dritan and Tomaszewski, Artur}},
issn = {{1110-757X}},
language = {{eng}},
publisher = {{Hindawi Limited}},
series = {{Journal of Applied Mathematics}},
title = {{Fair Optimization and Networks: A Survey}},
url = {{http://dx.doi.org/10.1155/2014/612018}},
doi = {{10.1155/2014/612018}},
year = {{2014}},
}