Using l^p-norms for Fairness in Combinatorial Optimisation

Bektas, Tolga ORCID: 0000-0003-0634-144X and Letchford, Adam N
(2020) Using l^p-norms for Fairness in Combinatorial Optimisation. Computers and Operations Research, 120. p. 104975.

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The issue of fairness has received attention from researchers in many fields, including combinatorial optimisation. One way to drive the solution toward fairness is to use a modified objective function that involves so-called l^p-norms. If done in a naive way, this approach leads to large and symmetric mixed-integer nonlinear programs (MINLPs), that may be difficult to solve. We show that, for some problems, one can obtain alternative MINLP formulations that are much smaller, do not suffer from symmetry, and have a reasonably tight continuous relaxation. We give encouraging computational results for certain vehicle routing, facility location and network design problems.

Item Type: Article
Uncontrolled Keywords: fairness, mixed-integer nonlinear programming, vehicle routing, facility location, network design
Depositing User: Symplectic Admin
Date Deposited: 24 Apr 2020 13:07
Last Modified: 18 Jan 2023 23:54
DOI: 10.1016/j.cor.2020.104975
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