2012
DOI: 10.1007/s11750-012-0252-x
|View full text |Cite
|
Sign up to set email alerts
|

Error minimization methods in biproportional apportionment

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
6
0

Year Published

2013
2013
2021
2021

Publication Types

Select...
4
1
1

Relationship

1
5

Authors

Journals

citations
Cited by 6 publications
(6 citation statements)
references
References 14 publications
0
6
0
Order By: Relevance
“…If the number of atomic voters is small then the corresponding inverse problem is exactly of the type investigated here. electoral systems, as discussed in Grilli di Cortona, Manzi, Pennisi, Ricca, and Simeone (1999), Pennisi, Ricca, Serafini, and Simeone (2007) or Ricca, Scozzari, Serafini, and Simeone (2012).…”
mentioning
confidence: 99%
“…If the number of atomic voters is small then the corresponding inverse problem is exactly of the type investigated here. electoral systems, as discussed in Grilli di Cortona, Manzi, Pennisi, Ricca, and Simeone (1999), Pennisi, Ricca, Serafini, and Simeone (2007) or Ricca, Scozzari, Serafini, and Simeone (2012).…”
mentioning
confidence: 99%
“…Our approach is obviously limited and the problem is open to several alternative approaches that deserve extra work. A particular one that deserves mention is the error minimization approach that has yielded a class of methods to solve biproportional apportionment problems (Ricca et al (2012) and Serafini and Simeone (2012)). These methods take a fractional matrix as the target (fair share table in our case) and solve a constrained optimization problem where the objective corresponds to a measure of the error between the solution and the target matrix.…”
Section: Discussionmentioning
confidence: 99%
“…One approach is based on characterizing proportionality via a set of axioms and finding the unique apportionment that satisfies them [1,2,14,8,5,6]. Another approach is based on finding an apportionment that minimizes a measure of deviation from given quotas [4,[15][16][17].…”
Section: Problem Statementmentioning
confidence: 99%
“…In the Controlled rounding procedure [4,16] the apportionment x ij must satisfy x ij ∈ { q ij , q ij }. Hence the problem may be rephrased by saying that one has to compute a binary matrix y ij ∈ {0, 1} that must satisfy the constraints…”
Section: A Certificate For the Controlled Rounding Apportionmentmentioning
confidence: 99%
See 1 more Smart Citation