Schulze method
The Schulze method is an electoral system developed in 1997 by Markus Schulze that selects a single winner using votes that express preferences. The method can also be used to create a sorted list of winners. The Schulze method is also known as Schwartz Sequential dropping, cloneproof Schwartz sequential dropping, the beatpath method, beatpath winner, path voting, and path winner.
The Schulze method is a Condorcet method, which means that if there is a candidate who is preferred by a majority over every other candidate in pairwise comparisons, then this candidate will be the winner when the Schulze method is applied.
The output of the Schulze method gives an ordering of candidates. Therefore, if several positions are available, the method can be used for this purpose without modification, by letting the k top-ranked candidates win the k available seats. Furthermore, for proportional representation elections, a single transferable vote variant has been proposed.
The Schulze method is used by several organizations including Debian, Ubuntu, Gentoo, Pirate Party political parties and [|many others].
Description of the method
Ballot
The input for the Schulze method is the same as for other ranked single-winner electoral systems: each voter must furnish an ordered preference list on candidates where ties are allowed.One typical way for voters to specify their preferences on a ballot is as follows. Each ballot lists all the candidates, and each voter ranks this list in order of preference using numbers: the voter places a '1' beside the most preferred candidate, a '2' beside the second-most preferred, and so forth. Each voter may optionally:
- give the same preference to more than one candidate. This indicates that this voter is indifferent between these candidates.
- use non-consecutive numbers to express preferences. This has no impact on the result of the elections, since only the order in which the candidates are ranked by the voter matters, and not the absolute numbers of the preferences.
- keep candidates unranked. When a voter doesn't rank all candidates, then this is interpreted as if this voter strictly prefers all ranked to all unranked candidates, and is indifferent among all unranked candidates.
Computation
A path from candidate to candidate is a sequence of candidates with the following properties:
- and.
- For all.
The strength of a path from candidate to candidate is the smallest number of voters in the sequence of comparisons:
For a pair of candidates and that are connected by at least one path, the strength of the strongest path is the maximum strength of the path connecting them. If there is no path from candidate to candidate at all, then.
Candidate is better than candidate if and only if.
Candidate is a potential winner if and only if for every other candidate.
It can be proven that and together imply. Therefore, it is guaranteed that the above definition of "better" really defines a transitive relation and that there is always at least one candidate with for every other candidate.
Example
In the following example 45 voters rank 5 candidates.The pairwise preferences have to be computed first. For example, when comparing and pairwise, there are voters who prefer to, and voters who prefer to. So and. The full set of pairwise preferences is:
labeled with pairwise preferences d
20 | 26 | 30 | 22 | ||
25 | 16 | 33 | 18 | ||
19 | 29 | 17 | 24 | ||
15 | 12 | 28 | 14 | ||
23 | 27 | 21 | 31 |
The cells for d have a light green background if d > d, otherwise the background is light red. There is no undisputed winner by only looking at the pairwise differences here.
Now the strongest paths have to be identified. To help visualize the strongest paths, the set of pairwise preferences is depicted in the diagram on the right in the form of a directed graph. An arrow from the node representing a candidate X to the one representing a candidate Y is labelled with d. To avoid cluttering the diagram, an arrow has only been drawn from X to Y when d > d, omitting the one in the opposite direction.
One example of computing the strongest path strength is p = 33: the strongest path from B to D is the direct path which has strength 33. But when computing p, the strongest path from A to C is not the direct path of strength 26, rather the strongest path is the indirect path which has strength min = 28. The strength of a path is the strength of its weakest link.
For each pair of candidates X and Y, the following table shows the strongest path from candidate X to candidate Y in red, with the weakest link underlined.
A | B | C | D | E | ||
A | A--D--C--B | A--D--C | A--D | A--D--C--E | A | |
B | B--A | B--D--C | B--D | B--D--C--E | B | |
C | C--B--A | C--B | C--B--D | C--E | C | |
D | D--C--B--A | D--C--B | D--C | D--C--E | D | |
E | E--D--C--B--A | E--D--C--B | E--D--C | E--D | E | |
A | B | C | D | E |
28 | 28 | 30 | 24 | ||
25 | 28 | 33 | 24 | ||
25 | 29 | 29 | 24 | ||
25 | 28 | 28 | 24 | ||
25 | 28 | 28 | 31 |
Now the output of the Schulze method can be determined. For example, when comparing and,
since, for the Schulze method candidate is better than candidate. Another example is that, so candidate E is better than candidate D. Continuing in this way, the result is that the Schulze ranking is, and wins. In other words, wins since for every other candidate X.
Implementation
The only difficult step in implementing the Schulze method is computing the strongest path strengths. However, this is a well-known problem in graph theory sometimes called the widest path problem. One simple way to compute the strengths, therefore, is a variant of the Floyd–Warshall algorithm. The following pseudocode illustrates the algorithm.- Input: d, the number of voters who prefer candidate i to candidate j.
- Output: p, the strength of the strongest path from candidate i to candidate j.
for j from 1 to C
if then
if then
p := d
else
p := 0
for i from 1 to C
for j from 1 to C
if then
for k from 1 to C
if then
p := max
This algorithm is efficient and has running time O where C is the number of candidates.
Ties and alternative implementations
When allowing users to have ties in their preferences, the outcome of the Schulze method naturally depends on how these ties are interpreted in defining d. Two natural choices are that d represents either the number of voters who strictly prefer A to B, or the margin of minus. But no matter how the ds are defined, the Schulze ranking has no cycles, and assuming the ds are unique it has no ties.Although ties in the Schulze ranking are unlikely, they are possible. Schulze's original paper proposed breaking ties in accordance with a voter selected at random, and iterating as needed.
An alternative way to describe the winner of the Schulze method is the following procedure:
- draw a complete directed graph with all candidates, and all possible edges between candidates
- iteratively delete all candidates not in the Schwartz set and delete the graph edge with the smallest value.
- the winner is the last non-deleted candidate.
- Make the results table, called the "matrix of pairwise preferences," such as used above in the example. If using margins rather than raw vote totals, subtract it from its transpose. Then every positive number is a pairwise win for the candidate on that row, ties are zeroes, and losses are negative. Order the candidates by how long they last in elimination.
- If there's a candidate with no red on their line, they win.
- Otherwise, draw a square box around the Schwartz set in the upper left corner. You can describe it as the minimal "winner's circle" of candidates who do not lose to anyone outside the circle. Note that to the right of the box there is no red, which means it's a winner's circle, and note that within the box there is no reordering possible that would produce a smaller winner's circle.
- Cut away every part of the table that isn't in the box.
- If there is still no candidate with no red on their line, something needs to be compromised on; every candidate lost some race, and the loss we tolerate the best is the one where the loser obtained the most votes. So, take the red cell with the highest number, make it green—or any color other than red—and go back step 2.
E | A | C | B | D | |
E | 1 | -3 | 9 | 17 | |
A | -1 | 7 | -5 | 15 | |
C | 3 | -7 | 13 | -11 | |
B | -9 | 5 | -13 | 21 | |
D | -17 | -15 | 11 | -21 |
The first drop doesn't help shrink the Schwartz set.
E | A | C | B | D | |
E | 1 | -3 | 9 | 17 | |
A | -1 | 7 | -5 | 15 | |
C | 3 | -7 | 13 | -11 | |
B | -9 | 5 | -13 | 21 | |
D | -17 | -15 | 11 | -21 |
So we get straight to the second drop, and that shows us the winner, E, with its clear row.
E | A | C | B | D | |
E | 1 | -3 | 9 | 17 | |
A | -1 | 7 | -5 | 15 | |
C | 3 | -7 | 13 | -11 | |
B | -9 | 5 | -13 | 21 | |
D | -17 | -15 | 11 | -21 |
This method can also be used to calculate a result, if you make the table in such a way that you can conveniently and reliably rearrange the order of the candidates on both row and column.
Satisfied and failed criteria
Satisfied criteria
The Schulze method satisfies the following criteria:- Unrestricted domain
- Non-imposition
- Non-dictatorship
- Pareto criterion
- Monotonicity criterion
- Majority criterion
- Majority loser criterion
- Condorcet criterion
- Condorcet loser criterion
- Schwartz criterion
- Smith criterion
- Independence of Smith-dominated alternatives
- Mutual majority criterion
- Independence of clones
- Reversal symmetry
- Mono-append
- Mono-add-plump
- Resolvability criterion
- Polynomial runtime
- prudence
- MinMax sets
- Woodall's plurality criterion if winning votes are used for d
- Symmetric-completion if margins are used for d
Failed criteria
Likewise, since the Schulze method is not a dictatorship and agrees with unanimous votes, Arrow's Theorem implies it fails the criterion
The Schulze method also fails
- Peyton Young's criterion Local Independence of Irrelevant Alternatives.
Comparison table
The main difference between the Schulze method and the ranked pairs method can be seen in this example:
Suppose the MinMax score of a set X of candidates is the strength of the strongest pairwise win of a candidate A ∉ X against a candidate B ∈ X. Then the Schulze method, but not Ranked Pairs, guarantees that the winner is always a candidate of the set with minimum MinMax score. So, in some sense, the Schulze method minimizes the largest majority that has to be reversed when determining the winner.
On the other hand, Ranked Pairs minimizes the largest majority that has to be reversed to determine the order of finish, in the minlexmax sense.
In other words, when Ranked Pairs and the Schulze method produce different orders of finish, for the majorities on which the two orders of finish disagree, the Schulze order reverses a larger majority than the Ranked Pairs order.
History
The Schulze method was developed by Markus Schulze in 1997. It was first discussed in public mailing lists in 1997–1998 and in 2000. Subsequently, Schulze method users included Debian, Gentoo, Topcoder, Wikimedia, KDE, the Pirate Party of Sweden, and the Pirate Party of Germany. In the French Wikipedia, the Schulze method was one of two multi-candidate methods approved by a majority in 2005, and it has been used several times. The newly formed Boise, Idaho chapter of the Democratic Socialists of America in February chose this method for their first special election held in March 2018.In 2011, Schulze published the method in the academic journal Social Choice and Welfare.
Users
The Schulze method is used by the city of Silla for all referendums. It is used by the Institute of Electrical and Electronics Engineers, by the Association for Computing Machinery, and by USENIX through their use of the HotCRP decision tool. The Schulze method is used by the cities of Turin and San Donà di Piave and by the London Borough of Southwark through their use of the WeGovNow platform, which in turn uses the LiquidFeedback decision tool. Organizations which currently use the Schulze method include:- AEGEE - European Students' Forum
- Annodex Association
- Associated Student Government at Northwestern University
- Associated Student Government at University of Freiburg
- Associated Student Government at the Computer Sciences Department of the University of Kaiserslautern
- :de:Berufsverband der Kinder- und Jugendärzte|Berufsverband der Kinder- und Jugendärzte
- BoardGameGeek
- Collective Agency
- County Highpointers
- Debian
- EuroBillTracker
- European Democratic Education Community
- FFmpeg
- Five Star Movement of Campobasso, Fondi, Monte Compatri, Montemurlo, Pescara, and San Cesareo
- Flemish Society of Engineering Students Leuven
- Free Geek
- Free Hardware Foundation of Italy
- Gentoo Foundation
- GNU Privacy Guard
- Graduate Student Organization at the State University of New York: Computer Science
- Haskell
- Hillegass Parker House
- Internet Corporation for Assigned Names and Numbers
- Kanawha Valley Scrabble Club
- KDE e.V.
- Kingman Hall
- Knight Foundation
- Kubuntu
- Kumoricon
- League of Professional System Administrators
- LiquidFeedback
- Metalab
- Music Television
- :de:Neo |Neo
- New Liberals
- Noisebridge
- OpenEmbedded
- OpenStack
- Pirate Party Australia
- Pirate Party of Austria
- Pirate Party of Belgium
- Pirate Party of Brazil
- Pirate Party of Germany
- Pirate Party of Iceland
- Pirate Party of Italy
- Pirate Party of the Netherlands
- Pirate Party of New Zealand
- Pirate Party of Sweden
- Pirate Party of Switzerland
- Pirate Party of the United States
- RLLMUK
- Squeak
- Students for Free Culture
- Sugar Labs
- SustainableUnion
- Sverok
- TestPAC
- TopCoder
- Ubuntu
- Vidya Gaem Awards
- Volt Europe
- Wikipedia in French, Hebrew, Hungarian, Russian, and Persian.