Using ℓp-norms for fairness in combinatorial optimisation

Bektas, Tolga and Letchford, Adam (2020) Using ℓp-norms for fairness in combinatorial optimisation. Computers and Operations Research, 120. ISSN 0305-0548

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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 ℓp-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.

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Journal Article
Journal or Publication Title:
Computers and Operations Research
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This is the author’s version of a work that was accepted for publication in Computers and Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Operations Research, 120, 2020 DOI: 10.1016/j.cor.2020.104975
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Deposited On:
20 Apr 2020 12:15
Last Modified:
11 May 2022 07:02