print("NCC")
# print(p)
print(word)
s.add(p)
if idx == MAX_DEPTH:
# print(word)
return
words(idx + 1, word + 'a')
words(idx + 1, word + 'b')
words(0, "")
# print("asserted constraints...")
# for c in s.assertions():
# print(c)
print()
print()
if s.check() == sat:
for item in utils.sorted_model(s):
print(item)
utils.z3_to_smt2(s, "ass1-q1")
else:
print("Failed to solve")
And(
Or(
CHIP_POS[i][0] <= (CHIP_POS[j][0] - POWER_COMPONENTS_DISTANCE - abs(COMPONENT_DIM[j][1] - COMPONENT_DIM[i][0])/2.), #left w/o rotation
CHIP_POS[j][0] <= (CHIP_POS[i][0] - POWER_COMPONENTS_DISTANCE - abs(COMPONENT_DIM[j][1] - COMPONENT_DIM[i][0])/2.), #right
CHIP_POS[i][1] <= (CHIP_POS[j][1] - POWER_COMPONENTS_DISTANCE - abs(COMPONENT_DIM[j][0] - COMPONENT_DIM[i][1])/2.), #below
CHIP_POS[j][1] <= (CHIP_POS[i][1] - POWER_COMPONENTS_DISTANCE - abs(COMPONENT_DIM[j][0] - COMPONENT_DIM[i][1])/2.), #above
),
And(CHIP_POS[i][2] == 0, CHIP_POS[j][2] == 1)
),
And(
Or(
CHIP_POS[i][0] <= (CHIP_POS[j][0] - POWER_COMPONENTS_DISTANCE - abs(COMPONENT_DIM[j][1] - COMPONENT_DIM[i][1])/2.), #left w/o rotation
CHIP_POS[j][0] <= (CHIP_POS[i][0] - POWER_COMPONENTS_DISTANCE - abs(COMPONENT_DIM[j][1] - COMPONENT_DIM[i][1])/2.), #right
CHIP_POS[i][1] <= (CHIP_POS[j][1] - POWER_COMPONENTS_DISTANCE - abs(COMPONENT_DIM[j][0] - COMPONENT_DIM[i][0])/2.), #below
CHIP_POS[j][1] <= (CHIP_POS[i][1] - POWER_COMPONENTS_DISTANCE - abs(COMPONENT_DIM[j][0] - COMPONENT_DIM[i][0])/2.), #above
),
And(CHIP_POS[i][2] == 1, CHIP_POS[j][2] == 1)
)
)
)
if s.check() == sat:
print(utils.sorted_model(s))
utils.draw_chip_design(CHIP_WIDTH, CHIP_HEIGHT, COMPONENT_DIM, POWER_COMPONENTS, s)
utils.z3_to_smt2(s, "ass1-q2")
else:
print("Failed to solve")
s.add(
And(SCHEDULE[11] >= SCHEDULE[8] + JOB_TIMES[8],
SCHEDULE[11] >= SCHEDULE[10] + JOB_TIMES[10]))
# Jobs 5,7 and 10 mutually exclusive
for i in [4, 6, 9]:
for j in [4, 6, 9]:
if not (i == j):
s.add(
Or(And(SCHEDULE[i] <= SCHEDULE[j] - JOB_TIMES[i]),
And(SCHEDULE[i] >= SCHEDULE[j] + JOB_TIMES[j])))
# Total time restriction
for i in range(JOBS):
s.add(SCHEDULE[i] <= TIME - JOB_TIMES[i])
# Additional condition for q3-b
# Job 6 and 12 need a resource of limited availability
# Job 6 can run only when job 12 is running
s.add(
And(SCHEDULE[5] >= SCHEDULE[11],
SCHEDULE[5] <= SCHEDULE[11] + JOB_TIMES[11] - JOB_TIMES[5]))
if s.check() == sat:
utils.sorted_model(s)
utils.z3_to_smt2(s, "ass1-q3-b")
utils.draw_schedule(JOBS, TIME, JOB_TIMES, s)
else:
print("Failed to solve")
truckItem[i][TYPEOF['Prittle']] == 0))
return s
while (True):
s = RepeatingFuntion(PRITTLES_GLOB)
if (s.check() == sat):
print("Satisfiable with " + str(PRITTLES_GLOB) + " prittle pallets")
PRITTLES_GLOB = PRITTLES_GLOB + 1
prev_solver = s
else:
print("Unsatisfiable with " + str(PRITTLES_GLOB) + " prittle pallets")
print("Best model found:\n")
print(utils.sorted_model(prev_solver))
utils.z3_to_smt2(prev_solver, "ass1-q1-b")
break
# if s.check() == sat:
# print(s.model())
# helper_obj = utils.helpers()
# helper_obj.z3_to_smt2(s.to_smt2(), "ass1-q1")
# else:
# print("Failed to solve")
# print(s.to_smt2())
var_constraints.append(
a[chosen_var][step] == a[chosen_var - 1][step - 1] +
a[chosen_var + 1][step - 1])
else:
var_constraints.append(a[i][step] == a[i][step - 1])
step_constraints.append(And(var_constraints))
s.add(Or(step_constraints))
# define the stop criteria a3 = a7
# a
s.add(a[3 - 1][STEPS - 1] == a[7 - 1][STEPS - 1])
# b
s.add(a[2][STEPS - 1] == a[4][STEPS - 1])
if s.check() == sat:
step = 0
for var, var_str in utils.sorted_model(s):
print(var, var_str)
step = step + 1
if step % NUM_VARS == 0:
print()
utils.z3_to_smt2(s, "ass1-q4-a")
else:
print("Failed to solve")