def tabu(N,NL,S,items, completion,tardiness,lambda1,lambda2): TL = [None]*NL pairs = generate.pairsets(S) completion_temp = completion[:] tardiness_temp = tardiness[:] delta_star = 0 Delta = 0 S_star = S[:] for k in xrange(N): delta = [] for s in pairs: if s not in TL: job = list(s) a = S[max(S.index(job[0]),S.index(job[1]))] b = S[min(S.index(job[0]),S.index(job[1]))] delta_c_a = - items[b].process delta_c_b = items[a].process delta_t_a = - min(items[b].process,tardiness_temp[a]) delta_t_b = max(completion_temp[a] - items[b].due,0) - tardiness_temp[b] wt_a,wt_b,wc_a,wc_b = items[a].wt,items[b].wt,items[a].wc,items[b].wc delta_a = h(delta_t_a,delta_c_a,wt_a,wc_a,lambda1,lambda2) delta_b = h(delta_t_b,delta_c_b,wt_b,wc_b,lambda1,lambda2) delta_h = delta_a + delta_b if delta == []: delta = delta_h delta_a_star = delta_a delta_b_star = delta_b a_star,b_star = a,b elif delta_h < delta: delta = delta_h delta_a_star = delta_a delta_b_star = delta_b a_star,b_star = a,b if delta == []: break a = S.index(a_star) b = S.index(b_star) S = generate.innerswap(S,a,b) change_set = set([a_star,b_star]) generate.pairsets_update(pairs,change_set) TL.pop(0) TL.append(change_set) completion_temp[a_star] -= items[b_star].process completion_temp[b_star] += items[a_star].process tardiness_temp[a_star] = max(completion_temp[a_star] - items[a_star].due,0) tardiness_temp[b_star] = max(completion_temp[b_star] - items[b_star].due,0) Delta += delta if Delta < delta_star: delta_star = Delta S_star = S[:] return delta_star,S_star
def value_generator(S,items,lambda1,lambda2): completion = complete_time(S,items) lateness = generate.late(completion,items) tardiness = generate.tard(lateness) item_values = [] for j in xrange(len(items)): item = items[j] wt,wc = item.wt,item.wc t,c = tardiness[j],completion[j] value = h(t,c,wt,wc,lambda1,lambda2) item_values.append(value) return completion,tardiness,item_values
def value_generator(S, items, lambda1, lambda2): # generate completion, tardniess, and item contribution values
completion = complete_time(S, items)
item = [items[j] for j in S]
lateness = generate.late(completion, item)
tardiness = generate.tard(lateness)
item_values = []
for j in xrange(len(item)):
itm = item[j]
wt, wc = itm.wt, itm.wc
t, c = tardiness[j], completion[j]
value = h(t, c, wt, wc, lambda1, lambda2)
item_values.append(value)
return completion, tardiness, item_values
def solve(input_data, N, NL, m, lambda1):
lambda2 = 1 - lambda1
Data = input_data.split("\n") # load data
n = len(Data) - 1 # get the amount of items
items = []
for j in xrange(n):
data = Data[j]
parts = data.split()
p = int(parts[0]) # get the process time
s = int(parts[2]) # get the setup time
d = int(parts[3]) # get the due date
wt = int(parts[4]) # get the tardiness weights
wc = int(parts[5]) # get the completion weights
items.append(Item(p + s, d, wt, wc)) # combine those item data
print "Data loaded!"
S, L, completion = generate.initialization(items, n, m)
lateness = generate.late(completion, items)
tardiness = generate.tard(lateness)
item_values = []
for j in xrange(len(items)):
item = items[j]
wt, wc = item.wt, item.wc
t, c = tardiness[j], completion[j]
value = h(t, c, wt, wc, lambda1, lambda2)
item_values.append(value)
print "Initialization done!"
G = generate.H(item_values, L)
line_values = []
for s in S:
value = generate.H(item_values, s)
line_values.append(value)
print "Initial values done!"
for l in xrange(m):
delta, S[l] = basictabu.tabu(1500, NL, S[l], items, completion, tardiness, lambda1, lambda2)
G += delta
line_values[l] += delta
completion, tardiness, item_values = generate.verify(S, items, lambda1, lambda2)
print "Initial Tabu Search Done!"
delta, S, L, line_values, item_values, completion, tardiness = tabu(
N, NL, S, L, items, completion, tardiness, line_values, item_values, G, lambda1, lambda2
)
G += delta
completion, tardiness, item_values = generate.verify(S, items, lambda1, lambda2)
u = tardiness.count(0)
cv = u / len(tardiness)
print tardiness
return G, cv, S
