def solve(input_data,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
r = int(parts[1]) # get the release 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,r,s,d,wt,wc)) # combine those item data
print 'Data loaded!'
S,L,completion,item_free = generate.initialization_c(items,n,m)
print 'Initialization done!'
line_values,G = generate.Goal(completion,items,S,lambda1,lambda2)
print 'Initialization values done!'
print G
NR = 19
item_values = h(S,completion,items,lambda1,lambda2)
for k in xrange(NR):
l_p,l_m = generate.reorder(items,S,line_values,item_values)
S[l_p],c_p = ATCS(items,S[l_p],m)
S[l_m],c_m = ATCS(items,S[l_m],m)
completion,line_values = complete_time(S,items,lambda1,lambda2)
item_values = h(S,completion,items,lambda1,lambda2)
G = sum(line_values)
Rb,c= generate.balance_rate(completion,S)
return G,Rb
def solve(input_data, 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
r = int(parts[1]) # get the release 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, r, s, d, wt, wc)) # combine those item data
print 'Data loaded!'
S, L, completion, item_free = generate.initialization_c(items, n, m)
print 'Initialization done!'
line_values, G = generate.Goal(completion, items, S, lambda1, lambda2)
print 'Initialization values done!'
print G
NR = 19
item_values = h(S, completion, items, lambda1, lambda2)
for k in xrange(NR):
l_p, l_m = generate.reorder(items, S, line_values, item_values)
S[l_p], c_p = ATCS(items, S[l_p], m)
S[l_m], c_m = ATCS(items, S[l_m], m)
completion, line_values = complete_time(S, items, lambda1, lambda2)
item_values = h(S, completion, items, lambda1, lambda2)
G = sum(line_values)
Rb, c = generate.balance_rate(completion, S)
return G, Rb
def solve(input_data, lambda1, N, NL, m):
lambda2 = 1 - lambda1
Data = input_data.split('\n') # load data
n = len(Data) - 1 # get the amount of items
m = 5
items = []
for j in xrange(n):
data = Data[j]
parts = data.split()
p = int(parts[0]) # get the process time
r = int(parts[1]) # get the release 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, r, s, d, wt, wc)) # combine those item data
print 'Data loaded!'
S, L, completion, item_free = generate.initialization_c(items, n, m)
print 'Initialization done!'
line_values, G = generate.Goal(completion, items, S, lambda1, lambda2)
print 'Initialization values done!'
print G
NR = 10
item_values = continueatcs.h(S, completion, items, lambda1, lambda2)
G_star = G
S_star = []
for s in S:
S_star.append(s[:])
for k in xrange(NR):
l_p, l_m = generate.reorder(items, S_star, line_values, item_values)
completion, line_values = continueatcs.complete_time(
S_star, items, lambda1, lambda2)
G_star = sum(line_values)
G_star, S_star, line_values, completion = tabu(N, NL, S_star, l_p,
items, G_star,
completion, line_values,
lambda1, lambda2)
G_star, S_star, line_values, completion = tabu(N, NL, S_star, l_m,
items, G_star,
completion, line_values,
lambda1, lambda2)
item_values = continueatcs.h(S_star, completion, items, lambda1,
lambda2)
Rb, _ = generate.balance_rate(completion, S)
completion, line_values = continueatcs.complete_time(
S_star, items, lambda1, lambda2)
return G_star, Rb
def solve(input_data,lambda1,N,NL,m):
lambda2 = 1 - lambda1
Data = input_data.split('\n') # load data
n = len(Data) -1 # get the amount of items
m = 5
items = []
for j in xrange(n):
data = Data[j]
parts = data.split()
p = int(parts[0]) # get the process time
r = int(parts[1]) # get the release 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,r,s,d,wt,wc)) # combine those item data
print 'Data loaded!'
S,L,completion,item_free = generate.initialization_c(items,n,m)
print 'Initialization done!'
line_values,G = generate.Goal(completion,items,S,lambda1,lambda2)
print 'Initialization values done!'
print G
NR = 10
item_values = continueatcs.h(S,completion,items,lambda1,lambda2)
G_star = G
S_star =[]
for s in S:
S_star.append(s[:])
for k in xrange(NR):
l_p,l_m = generate.reorder(items,S_star,line_values,item_values)
completion,line_values = continueatcs.complete_time(S_star,items,lambda1,lambda2)
G_star = sum(line_values)
G_star,S_star,line_values,completion = tabu(N,NL,S_star,l_p,items,G_star,completion,line_values,lambda1,lambda2)
G_star,S_star,line_values,completion = tabu(N,NL,S_star,l_m,items,G_star,completion,line_values,lambda1,lambda2)
item_values = continueatcs.h(S_star,completion,items,lambda1,lambda2)
Rb,_ = generate.balance_rate(completion,S)
completion,line_values = continueatcs.complete_time(S_star,items,lambda1,lambda2)
return G_star,Rb
def solve(input_data,m,lambda1,NR):
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)
print 'Initialization done!'
lateness = generate.late(completion,items) # begin the value initialization
tardiness = generate.tard(lateness)
item_values = []
for j in xrange(n):
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)
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 k in xrange(NR):
l_p,l_m = generate.reorder(items,S,line_values,item_values)
S[l_p],c_p = ATC(items,S[l_p])
S[l_m],c_m = ATC(items,S[l_m])
for j in S[l_p]:
completion[j] = c_p.pop(0)
c = completion[j]
item = items[j]
wt,wc = item.wt,item.wc
late = completion[j] - item.due
t = generate.tard(late)
item_values[j] = h(t[0],c,wt,wc,lambda1,lambda2)
for j in S[l_m]:
completion[j] = c_m.pop(0)
c = completion[j]
item = items[j]
wt,wc = item.wt,item.wc
late = completion[j] - item.due
t = generate.tard(late)
item_values[j] = h(t[0],c,wt,wc,lambda1,lambda2)
delta_p = generate.H(item_values,S[l_p]) - line_values[l_p]
delta_m = generate.H(item_values,S[l_m]) - line_values[l_m]
line_values[l_p] += delta_p
line_values[l_m] += delta_m
G = G + delta_m + delta_p
lateness = generate.late(completion,items)
tardiness = generate.tard(lateness)
u = tardiness.count(0)
cv = u/len(tardiness)
return G,cv,S
def solve(input_data,m,lambda1,N,NL,NR):
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)
print 'Initialization done!'
completion,tardiness,item_values = value_generator(S,items,lambda1,lambda2)
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]= tabu(N,NL,S[l],items,completion,tardiness,lambda1,lambda2)
G += delta
line_values[l] += delta
completion,tardiness,item_values = value_generator(S,items,lambda1,lambda2)
print 'Initial Tabu Search done!'
value = G
S_temp = [None]*m
for l in xrange(m):
S_temp[l] = S[l][:]
line_values_temp = line_values[:]
item_values_temp = item_values[:]
for k in xrange(NR):
l_p,l_m = generate.reorder(items,S_temp,line_values_temp,item_values_temp)
completion_temp,tardiness_temp,item_values_temp = value_generator(S_temp,items,lambda1,lambda2)
line_values_temp[l_p] = generate.H(item_values_temp,S_temp[l_p])
line_values_temp[l_m] = generate.H(item_values_temp,S_temp[l_m])
delta_p,S_temp[l_p] = tabu(N,NL,S_temp[l_p],items,completion_temp,tardiness_temp,lambda1,lambda2)
delta_m,S_temp[l_m] = tabu(N,NL,S_temp[l_m],items,completion_temp,tardiness_temp,lambda1,lambda2)
line_values_temp[l_p] += delta_p
line_values_temp[l_m] += delta_m
value = generate.H(item_values_temp,L)
value = value + delta_m + delta_p
if value < G:
G = value
line_values = line_values_temp[:]
completion,tardiness,item_values = value_generator(S_temp,items,lambda1,lambda2)
for l in xrange(m):
S[l] = S_temp[l][:]
print G
u = tardiness.count(0)
cv = u/len(tardiness)
print tardiness
return G,cv,S
def solve(input_data, m, lambda1, NR):
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)
print 'Initialization done!'
lateness = generate.late(completion,
items) # begin the value initialization
tardiness = generate.tard(lateness)
item_values = []
for j in xrange(n):
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)
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 k in xrange(NR):
l_p, l_m = generate.reorder(items, S, line_values, item_values)
S[l_p], c_p = ATC(items, S[l_p])
S[l_m], c_m = ATC(items, S[l_m])
for j in S[l_p]:
completion[j] = c_p.pop(0)
c = completion[j]
item = items[j]
wt, wc = item.wt, item.wc
late = completion[j] - item.due
t = generate.tard(late)
item_values[j] = h(t[0], c, wt, wc, lambda1, lambda2)
for j in S[l_m]:
completion[j] = c_m.pop(0)
c = completion[j]
item = items[j]
wt, wc = item.wt, item.wc
late = completion[j] - item.due
t = generate.tard(late)
item_values[j] = h(t[0], c, wt, wc, lambda1, lambda2)
delta_p = generate.H(item_values, S[l_p]) - line_values[l_p]
delta_m = generate.H(item_values, S[l_m]) - line_values[l_m]
line_values[l_p] += delta_p
line_values[l_m] += delta_m
G = G + delta_m + delta_p
lateness = generate.late(completion, items)
tardiness = generate.tard(lateness)
u = tardiness.count(0)
cv = u / len(tardiness)
return G, cv, S