def process(self, data):
instance = create_sudoku_model(data['board'])
var = instance.y[data['index']]
original_lb, original_ub = var.bounds
original_objective = instance.obj.expr
# check for tighter lower and upper bounds based on
# feasibility, and round to zero or one to eliminate
# the need for the client to handle solver
# tolerances
with SolverFactory('glpk') as solver:
instance.obj.expr = var
results = solver.solve(instance)
if results.solver.termination_condition == \
TerminationCondition.optimal:
var.setlb(int(round(var())))
instance.obj.expr = -var
results = solver.solve(instance)
if results.solver.termination_condition == \
TerminationCondition.optimal:
var.setub(int(round(var())))
instance.obj.expr = original_objective
if (var.lb > original_lb) or \
(var.ub < original_ub):
print("%s: new bounds %s" % (var, var.bounds))
else:
print("%s: no bound reduction" % (var))
return var.bounds
from pyomo.opt import (SolverFactory, TerminationCondition)
from sudoku import (create_sudoku_model, print_solution, add_integer_cut)
# define the board
board = [(1,1,5),(1,2,3),(1,5,7), \
(2,1,6),(2,4,1),(2,5,9),(2,6,5), \
(3,2,9),(3,3,8),(3,8,6), \
(4,1,8),(4,5,6),(4,9,3), \
(5,1,4),(5,4,8),(5,6,3),(5,9,1), \
(6,1,7),(6,5,2),(6,9,6), \
(7,2,6),(7,7,2),(7,8,8), \
(8,4,4),(8,5,1),(8,6,9),(8,9,5), \
(9,5,8),(9,8,7),(9,9,9)]
model = create_sudoku_model(board)
solution_count = 0
while 1:
with SolverFactory("glpk") as opt:
results = opt.solve(model)
if results.solver.termination_condition != \
TerminationCondition.optimal:
print("All board solutions have been found")
break
solution_count += 1
add_integer_cut(model)
print("Solution #%d" % (solution_count))
from sudoku import (create_sudoku_model,
print_solution,
add_integer_cut)
# define the board
board = [(1,1,5),(1,2,3),(1,5,7), \
(2,1,6),(2,4,1),(2,5,9),(2,6,5), \
(3,2,9),(3,3,8),(3,8,6), \
(4,1,8),(4,5,6),(4,9,3), \
(5,1,4),(5,4,8),(5,6,3),(5,9,1), \
(6,1,7),(6,5,2),(6,9,6), \
(7,2,6),(7,7,2),(7,8,8), \
(8,4,4),(8,5,1),(8,6,9),(8,9,5), \
(9,5,8),(9,8,7),(9,9,9)]
model = create_sudoku_model(board)
solution_count = 0
while 1:
with SolverFactory("glpk") as opt:
results = opt.solve(model)
if results.solver.termination_condition != \
TerminationCondition.optimal:
print("All board solutions have been found")
break
solution_count += 1
add_integer_cut(model)