def sym_wyzarzanie1(tasks_val, tasks, machines_val, T_start, T_end):
# pi0 = []
# for i in range(0, tasks_val):
# pi0.append(i)
# cmax0 = makespan(pi0, tasks, machines_val)
pi0, cmax0 = neh.neh(tasks, machines_val, tasks_val) #bierzemy z neha
pi = pi0
cmax_old = cmax0
T0 = T_start #temp poczatkowa
T = T0
u = 0.99 #wspolczynnik chlodzenia
Tgr = T_end #temp koncowa
while (T >= Tgr):
#piprim = swap(pi, tasks_val)
piprim = insert(pi, tasks_val) #uzywam inserta
cmax = neh.makespan(piprim, tasks, machines_val)
p = probability(cmax_old, cmax, T) #licze P wykonania kroku
s = ran.random()
if p >= s:
pi = piprim
cmax_old = cmax
T = chlodzenie1(T, u) #podstawowe chlodzenie
else:
T = chlodzenie1(T, u)
return pi, cmax_old
def sym_wyzarzanie2(tasks_val, tasks, machines_val, T_start, T_end, iter_val):
# pi0 = []
# for i in range(0, tasks_val):
# pi0.append(i)
# cmax0 = makespan(pi0, tasks, machines_val)
pi0, cmax0 = neh.neh(tasks, machines_val, tasks_val)
pi = pi0
cmax_old = cmax0
T0 = T_start
T = T0
u = 0.99
Tgr = T_end
iter = 0
max_iter = iter_val
for i in range(0, max_iter): #chlodzenie 2 jest na iteracje
iter = iter + 1
#piprim = swap(pi, tasks_val)
piprim = insert(pi, tasks_val)
cmax = neh.makespan(piprim, tasks, machines_val)
p = probability(cmax_old, cmax, T)
s = ran.random()
if p >= s:
pi = piprim
cmax_old = cmax
T = chlodzenie2(T, iter, max_iter)
else:
T = chlodzenie2(T, iter, max_iter)
#print(T)
if T == 0:
break
return pi, cmax_old
def sym_wyzarzanie4(tasks_val, tasks, machines_val, T_start, T_end):
# pi0 = []
# for i in range(0, tasks_val):
# pi0.append(i)
# cmax0 = makespan(pi0, tasks, machines_val)
pi0, cmax0 = neh.neh(tasks, machines_val, tasks_val)
pi = pi0
cmax_old = cmax0
T0 = T_start
T = T0
u = 0.99
Tgr = T_end
while (T >= Tgr):
#piprim = swap(pi, tasks_val)
piprim = insert(pi, tasks_val)
cmax = neh.makespan(piprim, tasks, machines_val)
if cmax_old != cmax:
p = probability4(cmax_old, cmax, T)
s = ran.random()
if p >= s:
pi = piprim
cmax_old = cmax
T = chlodzenie1(T, u)
else:
T = chlodzenie1(T, u)
return pi, cmax_old