Ejemplo n.º 1
0
def solve(input_data, N, NL, lambda1, m):
    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])
        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 'Initial values done!'

    for l in xrange(m):
        G, S, line_values, completion = continuetabu.tabu(
            N, NL, S, l, items, G, completion, line_values, lambda1, lambda2)
    G, S = tabu(N, NL, S, L, items, G, lambda1, lambda2)
    c, v = continueatcs.complete_time(S, items, lambda1, lambda2)
    Rb, _ = generate.balance_rate(completion, S)
    return G, Rb
Ejemplo n.º 2
0
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
Ejemplo n.º 3
0
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
Ejemplo n.º 4
0
def solve(input_data,N,NL,lambda1,m):
	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])
		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 'Initial values done!'

	for l in xrange(m):
		G,S,line_values,completion = continuetabu.tabu(N,NL,S,l,items,G,completion,line_values,lambda1,lambda2)
	G,S = tabu(N,NL,S,L,items,G,lambda1,lambda2)
	c,v = continueatcs.complete_time(S,items,lambda1,lambda2)
	Rb,_ = generate.balance_rate(completion,S)
	return G,Rb
Ejemplo n.º 5
0
def  h(S,completion,items,lambda1,lambda2):			# redefine the contribution of one item for the obj function
	n = len(items)
	lateness = generate.late(completion,items)
	value = [None]*n
	Rb,c_max = generate.balance_rate(completion,S)
	Ru = generate.idle_rate(items,completion,c_max,S)
	for s in S:
		l = S.index(s)
		for j in s:
			value[j] = lambda1*(math.fabs(items[j].wt*lateness[j]))/Ru[l] + lambda2*items[j].wc*completion[j]*math.exp(-Rb)
	return value
Ejemplo n.º 6
0
def h(S, completion, items, lambda1,
      lambda2):  # redefine the contribution of one item for the obj function
    n = len(items)
    lateness = generate.late(completion, items)
    value = [None] * n
    Rb, c_max = generate.balance_rate(completion, S)
    Ru = generate.idle_rate(items, completion, c_max, S)
    for s in S:
        l = S.index(s)
        for j in s:
            value[j] = lambda1 * (math.fabs(items[j].wt * lateness[j])) / Ru[
                l] + lambda2 * items[j].wc * completion[j] * math.exp(-Rb)
    return value
Ejemplo n.º 7
0
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
Ejemplo n.º 8
0
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