Ebert's method: Difference between revisions
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* Assume each voter approves at least one candidate. |
* Assume each voter approves at least one candidate. |
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A "load distribution" is a two-dimensional array X_{v,c} v=1 |
A "load distribution" is a two-dimensional array <math>X_{v,c}</math> with <math>v=1\ldots V,\,c=1\ldots C</math> such that: |
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# 0 |
# <math> 0 \leq X_{v,c} \leq 1</math> |
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# X_{v,c}=0 unless v approves c |
# <math>X_{v,c}=0</math> unless v approves c |
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# |
# <math>\sum_{v}\sum_{c}\,X_{v,c} = W</math> |
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# for each candidate c, |
# for each candidate c, <math>\sum_{v} X_{v,c} = 1</math> if c is a winner, otherwise <math>=0</math>. |
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The winner set is the set which minimizes |
The winner set is the set which minimizes <math>\sum_{v}(\sum_{c} X_{v,c} )^2</math>. |
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==Variants== |
==Variants== |