Schulze method
The Schulze method is a voting system developed by Markus Schulze that selects a single winner using votes that express preferences. The Schulze method can also be used to create a sorted list of winners. The Schulze method is also known as "Schwartz sequential dropping" (SSD), "cloneproof Schwartz sequential dropping" (CSSD), "beatpath method", "beatpath winner", "path voting", and "path winner".
If there is a candidate who is preferred over the other candidates, when compared in turn with each of the others, the Schulze method guarantees that that candidate will win. Because of this property, the Schulze method is (by definition) a Condorcet method. Note that this is different from some other preference voting systems such as Borda and Instant-runoff voting, which do not make this guarantee.
Many different heuristics for the Schulze method have been proposed. The most important heuristics are the path heuristic and the Schwartz set heuristic.
Contents
The path heuristic
Each ballot contains a complete list of all candidates. Each voter ranks these candidates in order of preference. The individual voter may give the same preference to more than one candidate and he may keep candidates unranked. When a given voter does not rank all candidates, then it is presumed that this voter strictly prefers all ranked candidates to all not ranked candidates and that this voter is indifferent between all not ranked candidates.
Procedure
Suppose d[V,W] is the number of voters who strictly prefer candidate V to candidate W.
A path from candidate X to candidate Y of strength p is a sequence of candidates C(1),...,C(n) with the following five properties:
- C(1) is identical to X.
- C(n) is identical to Y.
- For all i = 1,...,(n-1): d[C(i),C(i+1)] > d[C(i+1),C(i)].
- For all i = 1,...,(n-1): d[C(i),C(i+1)] ≥ p.
- For at least one i = 1,...,(n-1): d[C(i),C(i+1)] = p.
p[A,B], the strength of the strongest path from candidate A to candidate B, is the maximum value such that there is a path from candidate A to candidate B of that strength. If there is no path from candidate A to candidate B at all, then p[A,B] : = 0.
Candidate D is better than candidate E if and only if p[D,E] > p[E,D].
Candidate D is a potential winner if and only if p[D,E] ≥ p[E,D] for every other candidate E.
Implementation
Suppose C is the number of candidates. Then the strengths of the strongest paths can be calculated with the Floydâ€“Warshall algorithm.
Input: d[i,j] is the number of voters who strictly prefer candidate i to candidate j.
Output: Candidate i is a potential winner if and only if "winner[i] = true".
1 for i : = 1 to C 2 begin 3 for j : = 1 to C 4 begin 5 if ( i â‰ j ) then 6 begin 7 if ( d[i,j] > d[j,i] ) then 8 begin 9 p[i,j] : = d[i,j] 10 end 11 else 12 begin 13 p[i,j] : = 0 14 end 15 end 16 end 17 end 18 19 for i : = 1 to C 20 begin 21 for j : = 1 to C 22 begin 23 if ( i â‰ j ) then 24 begin 25 for k : = 1 to C 26 begin 27 if ( i â‰ k ) then 28 begin 29 if ( j â‰ k ) then 30 begin 31 p[j,k] : = max { p[j,k]; min { p[j,i]; p[i,k] } } 32 end 33 end 34 end 35 end 36 end 37 end 38 39 for i : = 1 to C 40 begin 41 winner[i] : = true 42 end 43 44 for i : = 1 to C 45 begin 46 for j : = 1 to C 47 begin 48 if ( i â‰ j ) then 49 begin 50 if ( p[j,i] > p[i,j] ) then 51 begin 52 winner[i] : = false 53 end 54 end 55 end 56 end
Examples
Example 1
Example (45 voters; 5 candidates):
- 5 ACBED
- 5 ADECB
- 8 BEDAC
- 3 CABED
- 7 CAEBD
- 2 CBADE
- 7 DCEBA
- 8 EBADC
d[*,A] | d[*,B] | d[*,C] | d[*,D] | d[*,E] | |
---|---|---|---|---|---|
d[A,*] | 20 | 26 | 30 | 22 | |
d[B,*] | 25 | 16 | 33 | 18 | |
d[C,*] | 19 | 29 | 17 | 24 | |
d[D,*] | 15 | 12 | 28 | 14 | |
d[E,*] | 23 | 27 | 21 | 31 |
The critical defeats of the strongest paths are underlined.
... to A | ... to B | ... to C | ... to D | ... to E | |
---|---|---|---|---|---|
from A ... | A-(30)-D-(28)-C-(29)-B | A-(30)-D-(28)-C | A-(30)-D | A-(30)-D-(28)-C-(24)-E | |
from B ... | B-(25)-A | B-(33)-D-(28)-C | B-(33)-D | B-(33)-D-(28)-C-(24)-E | |
from C ... | C-(29)-B-(25)-A | C-(29)-B | C-(29)-B-(33)-D | C-(24)-E | |
from D ... | D-(28)-C-(29)-B-(25)-A | D-(28)-C-(29)-B | D-(28)-C | D-(28)-C-(24)-E | |
from E ... | E-(31)-D-(28)-C-(29)-B-(25)-A | E-(31)-D-(28)-C-(29)-B | E-(31)-D-(28)-C | E-(31)-D |
p[*,A] | p[*,B] | p[*,C] | p[*,D] | p[*,E] | |
---|---|---|---|---|---|
p[A,*] | 28 | 28 | 30 | 24 | |
p[B,*] | 25 | 28 | 33 | 24 | |
p[C,*] | 25 | 29 | 29 | 24 | |
p[D,*] | 25 | 28 | 28 | 24 | |
p[E,*] | 25 | 28 | 28 | 31 |
Candidate E is a potential winner, because p[E,X] ≥ p[X,E] for every other candidate X.
Example 2
Example (30 voters; 4 candidates):
- 5 ACBD
- 2 ACDB
- 3 ADCB
- 4 BACD
- 3 CBDA
- 3 CDBA
- 1 DACB
- 5 DBAC
- 4 DCBA
d[*,A] | d[*,B] | d[*,C] | d[*,D] | |
---|---|---|---|---|
d[A,*] | 11 | 20 | 14 | |
d[B,*] | 19 | 9 | 12 | |
d[C,*] | 10 | 21 | 17 | |
d[D,*] | 16 | 18 | 13 |
The critical defeats of the strongest paths are underlined.
... to A | ... to B | ... to C | ... to D | |
---|---|---|---|---|
from A ... | A-(20)-C-(21)-B | A-(20)-C | A-(20)-C-(17)-D | |
from B ... | B-(19)-A | B-(19)-A-(20)-C | B-(19)-A-(20)-C-(17)-D | |
from C ... | C-(21)-B-(19)-A | C-(21)-B | C-(17)-D | |
from D ... | D-(18)-B-(19)-A | D-(18)-B | D-(18)-B-(19)-A-(20)-C |
p[*,A] | p[*,B] | p[*,C] | p[*,D] | |
---|---|---|---|---|
p[A,*] | 20 | 20 | 17 | |
p[B,*] | 19 | 19 | 17 | |
p[C,*] | 19 | 21 | 17 | |
p[D,*] | 18 | 18 | 18 |
Candidate D is a potential winner, because p[D,X] ≥ p[X,D] for every other candidate X.
Example 3
Example (30 voters; 5 candidates):
- 3 ABDEC
- 5 ADEBC
- 1 ADECB
- 2 BADEC
- 2 BDECA
- 4 CABDE
- 6 CBADE
- 2 DBECA
- 5 DECAB
d[*,A] | d[*,B] | d[*,C] | d[*,D] | d[*,E] | |
---|---|---|---|---|---|
d[A,*] | 18 | 11 | 21 | 21 | |
d[B,*] | 12 | 14 | 17 | 19 | |
d[C,*] | 19 | 16 | 10 | 10 | |
d[D,*] | 9 | 13 | 20 | 30 | |
d[E,*] | 9 | 11 | 20 | 0 |
The critical defeats of the strongest paths are underlined.
... to A | ... to B | ... to C | ... to D | ... to E | |
---|---|---|---|---|---|
from A ... | A-(18)-B | A-(21)-D-(20)-C | A-(21)-D | A-(21)-E | |
from B ... | B-(19)-E-(20)-C-(19)-A | B-(19)-E-(20)-C | B-(19)-E-(20)-C-(19)-A-(21)-D | B-(19)-E | |
from C ... | C-(19)-A | C-(19)-A-(18)-B | C-(19)-A-(21)-D | C-(19)-A-(21)-E | |
from D ... | D-(20)-C-(19)-A | D-(20)-C-(19)-A-(18)-B | D-(20)-C | D-(30)-E | |
from E ... | E-(20)-C-(19)-A | E-(20)-C-(19)-A-(18)-B | E-(20)-C | E-(20)-C-(19)-A-(21)-D |
p[*,A] | p[*,B] | p[*,C] | p[*,D] | p[*,E] | |
---|---|---|---|---|---|
p[A,*] | 18 | 20 | 21 | 21 | |
p[B,*] | 19 | 19 | 19 | 19 | |
p[C,*] | 19 | 18 | 19 | 19 | |
p[D,*] | 19 | 18 | 20 | 30 | |
p[E,*] | 19 | 18 | 20 | 19 |
Candidate B is a potential winner, because p[B,X] ≥ p[X,B] for every other candidate X.
Example 4
Example (9 voters; 4 candidates):
- 3 ABCD
- 2 DABC
- 2 DBCA
- 2 CBDA
d[*,A] | d[*,B] | d[*,C] | d[*,D] | |
---|---|---|---|---|
d[A,*] | 5 | 5 | 3 | |
d[B,*] | 4 | 7 | 5 | |
d[C,*] | 4 | 2 | 5 | |
d[D,*] | 6 | 4 | 4 |
The critical defeats of the strongest paths are underlined.
... to A | ... to B | ... to C | ... to D | |
---|---|---|---|---|
from A ... | A-(5)-B | A-(5)-C | A-(5)-C-(5)-D | |
from B ... | B-(5)-D-(6)-A | B-(7)-C | B-(5)-D | |
from C ... | C-(5)-D-(6)-A | C-(5)-D-(6)-A-(5)-B | C-(5)-D | |
from D ... | D-(6)-A | D-(6)-A-(5)-B | D-(6)-A-(5)-C |
p[*,A] | p[*,B] | p[*,C] | p[*,D] | |
---|---|---|---|---|
p[A,*] | 5 | 5 | 5 | |
p[B,*] | 5 | 7 | 5 | |
p[C,*] | 5 | 5 | 5 | |
p[D,*] | 6 | 5 | 5 |
Candidate B and candidate D are potential winners, because p[B,X] ≥ p[X,B] for every other candidate X and p[D,Y] ≥ p[Y,D] for every other candidate Y.
The Schwartz set heuristic
The Schwartz Set
The definition of a Schwartz set, as used in the Schulze method, is as follows:
- An unbeaten set is a set of candidates of whom none is beaten by anyone outside that set.
- An innermost unbeaten set is an unbeaten set that doesn't contain a smaller unbeaten set.
- The Schwartz set is the set of candidates who are in innermost unbeaten sets.
Procedure
The voters cast their ballots by ranking the candidates according to their preferences, just like for any other Condorcet election.
The Schulze method uses Condorcet pairwise matchups between the candidates and a winner is chosen in each of the matchups.
From there, the Schulze method operates as follows to select a winner (or create a ranked list):
- Calculate the Schwartz set based only on undropped defeats.
- If there are no defeats among the members of that set then they (plural in the case of a tie) win and the count ends.
- Otherwise, drop the weakest defeat among the candidates of that set. Go to 1.
An Example
The Situation
Imagine an election for the capital of Tennessee, a state in the United States that is over 500 miles east-to-west, and only 110 miles north-to-south. Let's say the candidates for the capital are Memphis (on the far west end), Nashville (in the center), Chattanooga (129 miles southeast of Nashville), and Knoxville (on the far east side, 114 northeast of Chattanooga). Here's the population breakdown by metro area (surrounding county):
- Memphis (Shelby County): 826,330
- Nashville (Davidson County): 510,784
- Chattanooga (Hamilton County): 285,536
- Knoxville (Knox County): 335,749
Let's say that in the vote, the voters vote based on geographic proximity. Assuming that the population distribution of the rest of Tennessee follows from those population centers, one could easily envision an election where the percentages of votes would be as follows:
42% of voters (close to Memphis) |
26% of voters (close to Nashville) |
15% of voters (close to Chattanooga) |
17% of voters (close to Knoxville) |
The results would be tabulated as follows:
A | |||||
---|---|---|---|---|---|
Memphis | Nashville | Chattanooga | Knoxville | ||
B | Memphis | [A] 58% [B] 42% | [A] 58% [B] 42% | [A] 58% [B] 42% | |
Nashville | [A] 42% [B] 58% | [A] 32% [B] 68% | [A] 32% [B] 68% | ||
Chattanooga | [A] 42% [B] 58% | [A] 68% [B] 32% | [A] 17% [B] 83% | ||
Knoxville | [A] 42% [B] 58% | [A] 68% [B] 32% | [A] 83% [B] 17% | ||
Pairwise election results (won-lost-tied): | 0-3-0 | 3-0-0 | 2-1-0 | 1-2-0 | |
Votes against in worst pairwise defeat: | 58% | N/A | 68% | 83% |
- [A] indicates voters who preferred the candidate listed in the column caption to the candidate listed in the row caption
- [B] indicates voters who preferred the candidate listed in the row caption to the candidate listed in the column caption
- [NP] indicates voters who expressed no preference between either candidate
Pairwise Winners
First, list every pair, and determine the winner:
Pair | Winner |
---|---|
Memphis (42%) vs. Nashville (58%) | Nashville 58% |
Memphis (42%) vs. Chattanooga (58%) | Chattanooga 58% |
Memphis (42%) vs. Knoxville (58%) | Knoxville 58% |
Nashville (68%) vs. Chattanooga (32%) | Nashville 68% |
Nashville (68%) vs. Knoxville (32%) | Nashville 68% |
Chattanooga (83%) vs. Knoxville (17%) | Chattanooga: 83% |
Note that absolute counts of votes can be used, or percentages of the total number of votes; it makes no difference.
Dropping
Next we start with our list of cities and their matchup wins/defeats
- Nashville 3-0
- Chattanooga 2-1
- Knoxville 1-2
- Memphis 0-3
Technically, the Schwartz set is simply Nashville as it beat all others 3 to 0.
Therefore, Nashville is the winner.
Ambiguity Resolution Example
Let's say there was an ambiguity. For a simple situation involving candidates A, B, and C.
- A > B 72%
- B > C 68%
- C > A 52%
In this situation the Schwartz set is A, B, and C as they all beat someone.
The Schulze method then says to drop the weakest defeat, so we drop C > A and are left with
- A > B 72% (as C has been removed)
Therefore, A is the winner.
(It may be more accessible to phrase that as "drop the weakest win", though purists may complain.)
Summary
In the (first) example election, the winner is Nashville. This would be true for any Condorcet method. Using the first-past-the-post system and some other systems, Memphis would have won the election by having the most people, even though Nashville won every simulated pairwise election outright. Using Instant-runoff voting in this example would result in Knoxville winning, even though more people preferred Nashville over Knoxville.
Satisfied Criteria
The Schulze method satisfies the following criteria:
- Mutual majority criterion
- Monotonicity criterion
- Pareto criterion
- Condorcet criterion
- Smith criterion (a.k.a. Generalized Condorcet criterion)
- local independence from irrelevant alternatives
- Schwartz criterion
- Plurality criterion
- the winner is always chosen from the Immune set
- the winner is always chosen from the CDTT set
- Minimal Defense criterion
- Strategy-Free criterion
- Generalized Strategy-Free criterion
- Strong Defensive Strategy criterion
- Weak Defensive Strategy criterion
- Summability criterion
- Independence of clones
- Neutrality of Spoiled Ballots
The Schulze method violates the following criteria:
- Participation criterion
- Consistency criterion
- invulnerability to compromising
- invulnerability to burying
- Favorite Betrayal criterion
- Later-no-harm criterion
History of the Schulze method
The Schulze method was developed by Markus Schulze in 1997. The first time that the Schulze method was discussed in a public mailing list was in 1998 [1] [2] [3] [4] [5]. In the following years, the Schulze method has been adopted e.g. by "Software in the Public Interest" (2003), Debian (2003), Gentoo (2005), TopCoder (2005), and "Sender Policy Framework" (2005). The first books on the Schulze method were written by Tideman (2006) and by Stahl and Johnson (2007).
Use of the Schulze method
The Schulze method is not currently used in government elections. However, it is starting to receive support in some public organizations. Organizations which currently use the Schulze method are:
- Annodex Association [6]
- Blitzed [7]
- BoardGameGeek [8] [9] [10]
- Codex Alpe Adria [11]
- College of Marine Science [12]
- Computer Science Departmental Society for York University (HackSoc) [13]
- County Highpointers [14]
- Debian [15] [16] [17]
- Digital Freedom in Education and Youth [18]
- EnMasse Forums
- EuroBillTracker [19] [20] [21] [22]
- European Democratic Education Conference [23]
- Fair Trade Northwest (see article XI section 2 of their bylaws)
- Free Hardware Foundation of Italy [24] [25]
- Free Software Foundation Europe (FSFE) (see article 6 section 3 of the constitution)
- Free Software Foundation Latin America (FSFLA) [26] [27]
- Gentoo Foundation [28] [29] [30] [31] [32] [33]
- GNU Privacy Guard (GnuPG) [34]
- Kingman Hall [35] [36]
- Kumoricon [37] [38] [39]
- Libertarian Party at Colorado State University (LPCSU) [40]
- Mathematical Knowledge Management Interest Group (MKM-IG) (The MKM-IG uses Condorcet with dual dropping. That means: The Schulze ranking and the ranked pairs ranking are calculated and the winner is the top-ranked candidate of that of these two rankings that has the better Kemeny score.) [41] [42] [43] [44]
- Metalab [45]
- Music Television (MTV) [46]
- North Shore Cyclists (NSC) [47] [48]
- OpenCouchSurfing [49]
- Pittsburgh Ultimate [50]
- RPMrepo [51]
- Sender Policy Framework (SPF) [52] [53] [54]
- Software in the Public Interest (SPI) [55]
- Students for Free Culture [56] [57]
- TopCoder [58] [59] [60] [61] [62] [63] [64] [65] [66] [67]
- Wikimedia Foundation [68]
- Wikipedia in French (The Schulze method is one of three methods recommended for decision-making.) [69]
- Wikipedia in Hungarian [70] [71]
- Wikipedia in Spanish [72]
External Resources
General
- Proposed Statutory Rules for the Schulze Single-Winner Election Method by Markus Schulze
- A New Monotonic and Clone-Independent Single-Winner Election Method by Markus Schulze (mirrors: [73] [74])
- A New Monotonic, Clone-Independent, Reversal Symmetric, and Condorcet-Consistent Single-Winner Election Method by Markus Schulze
- Free Riding and Vote Management under Proportional Representation by the Single Transferable Vote by Markus Schulze
- Implementing the Schulze STV Method by Markus Schulze
- A New MMP Method by Markus Schulze
- A New MMP Method (Part 2) by Markus Schulze
Tutorials
- Schulze-Methode by the University of Stuttgart
Advocacy
- Election Methods Resource by Blake Cretney
- Voting Methods Survey by James Green-Armytage
- Descriptions of ranked-ballot voting methods by Rob LeGrand
- Accurate Democracy by Rob Loring
- Schulze beatpaths method by Warren D. Smith
- Election Methods and Criteria by Kevin Venzke
- The Debian Voting System by Jochen Voss
- election-methods: a mailing list containing technical discussions about election methods
Research papers
- Social Choice Under Incomplete, Cyclic Preferences by Jobst Heitzig
- Voting Systems by Paul E. Johnson
- Distance from Consensus: a Theme and Variations by Tommi Meskanen and Hannu Nurmi
- Analyzing Political Disagreement by Tommi Meskanen and Hannu Nurmi
- Descriptions of voting systems by Warren D. Smith
- Election Systems by Peter A. Taylor
- Personalisierung der VerhÃ¤ltniswahl durch Varianten der Single Transferable Vote by Martin Wilke
- Approaches to Constructing a Stratified Merged Knowledge Base by Anbu Yue, Weiru Liu, and Anthony Hunter
Books
- Understanding Modern Mathematics by Saul Stahl and Paul E. Johnson (ISBN 0-7637-3401-2)
- Collective Decisions and Voting: The Potential for Public Choice [75] by Nicolaus Tideman (ISBN 0-7546-4717-X)
Software
- Voting Software Project by Blake Cretney
- Condorcet with Dual Dropping Perl Scripts by Mathew Goldstein
- Condorcet Voting Calculator by Eric Gorr
- Selectricity and RubyVote by Benjamin Mako Hill
- Java implementation of the Schulze method by Thomas Hirsch
- Electowidget by Rob Lanphier
- Haskell Condorcet Module by Evan Martin
- Condorcet Internet Voting Service (CIVS) by Andrew Myers
- BetterPolls.com by Brian Olson
Legislative project
- Condorcet Policy "Think Tank" moderated by Jeffry R. Fisher
- Arizonans for Competitive Elections Reform [76] [77] [78] [79] [80]
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