generic_binary_constraint
generic_binary_constraint |
Purpose
This constraint can be used to propagate a user-defined constraint over two variables (its propagation is based on the AC2001 algorithm (cf.
[Bes01]).
Synopsis
function generic_binary_constraint(v1:cpvar,v2:cpvar, fctname:string) : cpctr
Arguments
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v1
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the first decision variable
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|
v2
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the second decision variable
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fctname
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name of the function specifying the user-defined constraint, such a function necessarily takes two cpvar as arguments and returns a Boolean.
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Return value
A binary constraint over 'v1' and 'v2'
Example
The following example shows how to use the generic_binary_constraint constraint to solve the classical Euler Knight Tour problem:
model "Euler Knight Moves"
uses "kalis"
parameters
S = 8 ! No. of rows/columns
end-parameters
N:= S * S ! Total number of cells
setparam("KALIS_DEFAULT_LB", 0)
setparam("KALIS_DEFAULT_UB", N-1)
forward public function valid_knight_move(a:integer, b:integer): boolean
declarations
PATH = 1..N ! Cells on the board
pos: array(PATH) of cpvar ! Position p in tour
end-declarations
! Setting names of decision variables
forall(i in PATH) setname(pos(i), "Position"+i)
! Fix the start position
pos(1) = 0
! Each cell is visited once
all_different(pos, KALIS_GEN_ARC_CONSISTENCY)
! The knight's path obeys the chess rules for valid knight moves
forall(i in 1..N-1)
generic_binary_constraint(pos(i), pos(i+1), "valid_knight_move")
generic_binary_constraint(pos(N), pos(1), "valid_knight_move")
! Setting enumeration parameters
cp_set_branching(probe_assign_var(KALIS_SMALLEST_MIN,
KALIS_MAX_TO_MIN, pos, 14))
! Search for up to NBSOL solutions
solct:= 0
if not cp_find_next_sol then
writeln("No solution")
else
writeln(pos)
end-if
! **** Test whether the move from a to b is admissible ****
public function valid_knight_move(a:integer, b:integer): boolean
declarations
xa,ya,xb,yb,delta_x,delta_y: integer
end-declarations
xa := a div S
ya := a mod S
xb := b div S
yb := b mod S
delta_x := abs(xa-xb)
delta_y := abs(ya-yb)
returned := (delta_x<=2) and (delta_y<=2) and (delta_x+delta_y=3)
end-function
end-model
