Operations research methods in political decisions: a case study on the European Parliament composition

Janusz Łyko , Radosław Rudek

Abstract

In this paper, we show that operations research methods can be successfully applied to support decision-making in politics on the case study of the apportionment of seats in the European Parliament. The related political constraints and assumptions are quantitatively described and the optimization problem is formulated. On this basis, it is revealed that the current composition of the European Parliament as well as some intuitive propositions do not respect degressive proportionality as far as it was assumed. Nevertheless, our algorithm allows us to find better solutions, and among them, there is only one best allocation, which respects degressive proportionality as far as possible, according to the well known and often applied measures. Namely, over 9 thousands allocations consistent with the political requirement “nobody gains and nobody loses more than one” are referred to over 5.4 millions degressively proportional solutions, and only one allocation is revealed to be the best for all defined criteria under given populations of countries
Author Janusz Łyko (MISaF / IZM / KMiC)
Janusz Łyko,,
- Katedra Matematyki i Cybernetyki
, Radosław Rudek (MISaF / IBI / DIT)
Radosław Rudek,,
- Department of Information Technologies
Journal seriesComputational and Mathematical Organization Theory, ISSN 1381-298X, e-ISSN 1572-9346, (A 25 pkt)
Issue year2017
Vol23
No4
Pages572-586
Publication size in sheets0.7
Keywords in EnglishDecision support systemsOR methodsAllocationDegressive proportionalityGovernmentEuropean Parliament
ASJC Classification2604 Applied Mathematics; 2605 Computational Mathematics; 2611 Modelling and Simulation; 1700 General Computer Science; 1800 General Decision Sciences
DOIDOI:10.1007/s10588-017-9243-7
Languageen angielski
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Lyko_Rudek_Operations_ research_ methods2017.pdf 822,82 KB
Score (nominal)25
Publication indicators WoS Citations = 0; Scopus Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 0.637; WoS Impact Factor: 2017 = 0.641 (2) - 2017=1.102 (5)
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