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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
v1 
the first decision variable
v2 
the second decision variable
fctname 
name of the function specifying the user-defined constraint, such a function necessarily takes two cpvar as arguments and returns a Boolean.
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)

 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 ****
 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


Parent Topic Constraints