The Fourier-Motzkin elimination procedure #
The Fourier-Motzkin procedure is a variable elimination method for linear inequalities. https://en.wikipedia.org/wiki/Fourier%E2%80%93Motzkin_elimination
Given a set of linear inequalities comps = {tᵢ Rᵢ 0}
,
we aim to eliminate a single variable a
from the set.
We partition comps
into comps_pos
, comps_neg
, and comps_zero
,
where comps_pos
contains the comparisons tᵢ Rᵢ 0
in which
the coefficient of a
in tᵢ
is positive, and similar.
For each pair of comparisons tᵢ Rᵢ 0 ∈ comps_pos
, tⱼ Rⱼ 0 ∈ comps_neg
,
we compute coefficients vᵢ, vⱼ ∈ ℕ
such that vᵢ*tᵢ + vⱼ*tⱼ
cancels out a
.
We collect these sums vᵢ*tᵢ + vⱼ*tⱼ R' 0
in a set S
and set comps' = S ∪ comps_zero
,
a new set of comparisons in which a
has been eliminated.
Theorem: comps
and comps'
are equisatisfiable.
We recursively eliminate all variables from the system. If we derive an empty clause 0 < 0
,
we conclude that the original system was unsatisfiable.
Datatypes #
The CompSource
and PComp
datatypes are specific to the FM elimination routine;
they are not shared with other components of linarith
.
- assump: ℕ → Linarith.CompSource
- add: Linarith.CompSource → Linarith.CompSource → Linarith.CompSource
- scale: ℕ → Linarith.CompSource → Linarith.CompSource
CompSource
tracks the source of a comparison.
The atomic source of a comparison is an assumption, indexed by a natural number.
Two comparisons can be added to produce a new comparison,
and one comparison can be scaled by a natural number to produce a new comparison.
Instances For
Equations
- Linarith.instInhabitedCompSource = { default := Linarith.CompSource.assump default }
Given a CompSource
cs
, cs.flatten
maps an assumption index
to the number of copies of that assumption that appear in the history of cs
.
For example, suppose cs
is produced by scaling assumption 2 by 5,
and adding to that the sum of assumptions 1 and 2.
cs.flatten
maps 1 ↦ 1, 2 ↦ 6
.
Equations
- Linarith.CompSource.flatten (Linarith.CompSource.assump n) = Std.HashMap.insert Std.HashMap.empty n 1
- Linarith.CompSource.flatten (Linarith.CompSource.add c1 c2) = Std.HashMap.mergeWith (fun x b b' => b + b') (Linarith.CompSource.flatten c1) (Linarith.CompSource.flatten c2)
- Linarith.CompSource.flatten (Linarith.CompSource.scale n c) = Std.HashMap.mapVal (fun x v => v * n) (Linarith.CompSource.flatten c)
Instances For
Formats a CompSource
for printing.
Equations
- Linarith.CompSource.toString (Linarith.CompSource.assump n) = toString n
- Linarith.CompSource.toString (Linarith.CompSource.add c1 c2) = Linarith.CompSource.toString c1 ++ " + " ++ Linarith.CompSource.toString c2
- Linarith.CompSource.toString (Linarith.CompSource.scale n c) = toString n ++ " * " ++ Linarith.CompSource.toString c
Instances For
Equations
- Linarith.instToFormatCompSource = { format := fun a => Std.Format.text (Linarith.CompSource.toString a) }
- c : Linarith.Comp
The comparison
Σ cᵢ*xᵢ R 0
. - src : Linarith.CompSource
We track how the comparison was constructed by adding and scaling previous comparisons, back to the original assumptions.
The set of original assumptions which have been used in constructing this comparison.
The variables which have been effectively eliminated, i.e. by running the elimination algorithm on that variable.
The variables which have been implicitly eliminated. These are variables that appear in the historical set, do not appear in
c
itself, and are not in `effective.The union of all variables appearing in those original assumptions which appear in the
history
set.
A PComp
stores a linear comparison Σ cᵢ*xᵢ R 0
,
along with information about how this comparison was derived.
The original expressions fed into linarith
are each assigned a unique natural number label.
The historical set PComp.history
stores the labels of expressions
that were used in deriving the current PComp
.
Variables are also indexed by natural numbers. The sets PComp.effective
, PComp.implicit
,
and PComp.vars
contain variable indices.
PComp.vars
contains the variables that appear in any inequality in the historical set.PComp.effective
contains the variables that have been effectively eliminated fromPComp
. A variablen
is said to be effectively eliminated inp : PComp
if the elimination ofn
produced at least one of the ancestors ofp
(orp
itself).PComp.implicit
contains the variables that have been implicitly eliminated fromPComp
. A variablen
is said to be implicitly eliminated inp
if it satisfies the following properties:
We track these sets in order to compute whether the history of a PComp
is minimal.
Checking this directly is expensive, but effective approximations can be defined in terms of these
sets. During the variable elimination process, a PComp
with non-minimal history can be discarded.
Instances For
Any comparison whose history is not minimal is redundant,
and need not be included in the new set of comparisons.
elimedGE : ℕ
is a natural number such that all variables with index ≥ elimedGE
have been
removed from the system.
This test is an overapproximation to minimality. It gives necessary but not sufficient conditions.
If the history of c
is minimal, then c.maybeMinimal
is true,
but c.maybeMinimal
may also be true for some c
with non-minimal history.
Thus, if c.maybeMinimal
is false, c
is known not to be minimal and must be redundant.
See https://doi.org/10.1016/B978-0-444-88771-9.50019-2 (Theorem 13).
The condition described there considers only implicitly eliminated variables that have been
officially eliminated from the system. This is not the case for every implicitly eliminated
variable. Consider eliminating z
from {x + y + z < 0, x - y - z < 0}
. The result is the set
{2*x < 0}
; y
is implicitly but not officially eliminated.
This implementation of Fourier-Motzkin elimination processes variables in decreasing order of
indices. Immediately after a step that eliminates variable k
, variable k'
has been eliminated
iff k' ≥ k
. Thus we can compute the intersection of officially and implicitly eliminated variables
by taking the set of implicitly eliminated variables with indices ≥ elimedGE
.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The src : CompSource
field is ignored when comparing PComp
s. Two PComp
s proving the same
comparison, with different sources, are considered equivalent.
Equations
- Linarith.PComp.cmp p1 p2 = Linarith.Comp.cmp p1.c p2.c
Instances For
PComp.scale c n
scales the coefficients of c
by n
and notes this in the CompSource
.
Equations
- Linarith.PComp.scale c n = { c := Linarith.Comp.scale c.c n, src := Linarith.CompSource.scale n c.src, history := c.history, effective := c.effective, implicit := c.implicit, vars := c.vars }
Instances For
PComp.add c1 c2 elimVar
creates the result of summing the linear comparisons c1
and c2
,
during the process of eliminating the variable elimVar
.
The computation assumes, but does not enforce, that elimVar
appears in both c1
and c2
and does not appear in the sum.
Computing the sum of the two comparisons is easy; the complicated details lie in tracking the
additional fields of PComp
.
- The historical set
pcomp.history
ofc1 + c2
is the union of the two historical sets. vars
is the union ofc1.vars
andc2.vars
.- The effectively eliminated variables of
c1 + c2
are the union of the two effective sets, withelim_var
inserted. - The implicitly eliminated variables of
c1 + c2
are those that appear invars
but notc.vars
oreffective
. (Note that the description of the implicitly eliminated variables ofc1 + c2
in the algorithm described in Section 6 of https://doi.org/10.1016/B978-0-444-88771-9.50019-2 seems to be wrong: that says it should be(c1.implicit.union c2.implicit).sdiff explicit
. Since the implicitly eliminated sets start off empty for the assumption, this formula would leave them always empty.)
Equations
- One or more equations did not get rendered due to their size.
Instances For
PComp.assump c n
creates a PComp
whose comparison is c
and whose source is
CompSource.assump n
, that is, c
is derived from the n
th hypothesis.
The history is the singleton set {n}
.
No variables have been eliminated (effectively or implicitly).
Equations
- One or more equations did not get rendered due to their size.
Instances For
Equations
- Linarith.instToFormatPComp = { format := fun p => Std.format p.c.coeffs ++ Std.Format.text (toString p.c.str) ++ Std.Format.text "0" }
A collection of comparisons.
Instances For
Elimination procedure #
If c1
and c2
both contain variable a
with opposite coefficients,
produces v1
and v2
such that a
has been cancelled in v1*c1 + v2*c2
.
Equations
- One or more equations did not get rendered due to their size.
Instances For
pelimVar p1 p2
calls elimVar
on the Comp
components of p1
and p2
.
If this returns v1
and v2
, it creates a new PComp
equal to v1*p1 + v2*p2
,
and tracks this in the CompSource
.
Equations
- One or more equations did not get rendered due to their size.
Instances For
A PComp
represents a contradiction if its Comp
field represents a contradiction.
Equations
Instances For
elimWithSet a p comps
collects the result of calling pelimVar p p' a
for every p' ∈ comps
.
Equations
- One or more equations did not get rendered due to their size.
Instances For
- maxVar : ℕ
The largest variable index that has not been (officially) eliminated.
- comps : Linarith.PCompSet
The set of comparisons.
The state for the elimination monad.
The elimination procedure proceeds by eliminating variable v
from comps
progressively
in decreasing order.
Instances For
The linarith monad extends an exceptional monad with a LinarithData
state.
An exception produces a contradictory PComp
.
Instances For
Returns the current max variable.
Equations
Instances For
Return the current comparison set.
Equations
Instances For
Throws an exception if a contradictory PComp
is contained in the current state.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Updates the current state with a new max variable and comparisons,
and calls validate
to check for a contradiction.
Equations
- Linarith.update maxVar comps = do StateT.set { maxVar := maxVar, comps := comps } Linarith.validate
Instances For
splitSetByVarSign a comps
partitions the set comps
into three parts.
pos
contains the elements ofcomps
in whicha
has a positive coefficient.neg
contains the elements ofcomps
in whicha
has a negative coefficient.notPresent
contains the elements ofcomps
in whicha
has coefficient 0.
Returns (pos, neg, notPresent)
.
Equations
- One or more equations did not get rendered due to their size.
Instances For
elimVarM a
performs one round of Fourier-Motzkin elimination, eliminating the variable a
from the linarith
state.
Equations
- One or more equations did not get rendered due to their size.
Instances For
elimAllVarsM
eliminates all variables from the linarith state, leaving it with a set of
ground comparisons. If this succeeds without exception, the original linarith
state is consistent.
Equations
- One or more equations did not get rendered due to their size.
Instances For
mkLinarithData hyps vars
takes a list of hypotheses and the largest variable present in
those hypotheses. It produces an initial state for the elimination monad.
Equations
- One or more equations did not get rendered due to their size.
Instances For
produceCertificate hyps vars
tries to derive a contradiction from the comparisons in hyps
by eliminating all variables ≤ maxVar
.
If successful, it returns a map coeff : ℕ → ℕ
as a certificate.
This map represents that we can find a contradiction by taking the sum ∑ (coeff i) * hyps[i]
.
Equations
- One or more equations did not get rendered due to their size.