def apply(item, bins):
"""
Adds the item to the next available bin after the last insertion.
:param item: The item to add.
:param bins: The bins to choose from.
:return: The list of bins after insertion.
"""
b = bins[-1]
if not b.add_item(item):
b = Bin(bins[0].capacity)
bins.append(b)
b.add_item(item)
return bins
def apply(item, bins):
"""
Adds the item to the very first bin that it can fit it.
:param item: The item to add.
:param bins: The bins to choose from.
:return: The list of bins after the insertion.
"""
b = next((b for b in bins if b.can_add_item(item)), None)
if not b:
b = Bin(bins[0].capacity)
bins.append(b)
b.add_item(item)
return bins
def apply(item, bins):
"""
Adds the item to the bin for which the most amount of open space would be available after insertion.
:param item: The item to add.
:param bins: The bins to choose from.
:return: The list of bins after insertion.
"""
valid_bins = (b for b in bins if b.can_add_item(item))
sorted_bins = sorted(valid_bins, key=lambda x: x.filled_space())
if sorted_bins:
b = sorted_bins[0]
else:
b = Bin(bins[0].capacity)
bins.append(b)
b.add_item(item)
return bins
def execDir(self):
global pathh
pat = pathh
files = listdir(pathh)
open("result_ff.csv", "w").close()
print(1)
print(pat)
for f in files:
l = pat + "/" + f
print(f)
j = self.InstanceReader2(f)
print("hada", j)
instance, n, C, w = self.InstanceReader(l)
print("hadddd")
items = [Item(size=int(i)) for i in w]
shuffle(items)
start = timeit.default_timer()
bins = [Bin(capacity=C)]
for item in items:
bins = FirstFit.apply(item, bins)
stop = timeit.default_timer()
time = stop - start
c = len(bins)
resultatt = open("result_ff.csv", mode="a+")
resultatt.write(f'{instance},{n},{C},{c},{j},{time * 1000}\n') # Ecrire les resultats dans un fichier csv
resultatt.close()
print(pathh)
self.loadData_mod_csv('./result_ff.csv')
def apply(item, bins):
"""
Adds the item to the bin for which the least amount of open space would be available after insertion.
:param item: The item to add.
:param bins: The bins to choose from.
:return: The list of bins after the insertion.
"""
valid_bins = (b for b in bins if b.can_add_item(item))
# Note that this method is exactly the same as for the BestFit heuristic except for the following line.
sorted_bins = sorted(valid_bins, key=lambda x: x.filled_space(), reverse=True)
if sorted_bins:
b = sorted_bins[0]
else:
b = Bin(bins[0].capacity)
bins.append(b)
b.add_item(item)
return bins
def generate_solution(self, items):
"""
Generates a candidate solution based on the pattern given.
:param items: The items that need to be used when generating a solution.
:return: A list of bins to serve as a solution.
"""
solution = [Bin(self.bin_capacity)]
pattern_length = len(self.pattern)
for idx, item in enumerate(items):
h = self.pattern[idx % pattern_length]
solution = self.heuristic_map[h].apply(item, solution)
return solution
def exeFile(self):
global pathh
a_file = open(pathh, "r")
print(pathh, 111)
list_of_lists = []
for line in a_file:
stripped_line = line.strip()
# line_list = stripped_line.split()
n_liste = int(stripped_line)
list_of_lists.append(n_liste)
a_file.close()
weight = list_of_lists[2:]
# print(weight)
C = list_of_lists[1]
print(C)
items = [Item(size=int(i)) for i in weight]
shuffle(items)
start = timeit.default_timer()
bins = [Bin(capacity=C)]
print(1)
for item in items:
print(item)
bins = BestFit.apply(item, bins)
print(2)
stop = timeit.default_timer()
time = stop - start
c = len(bins)
#c, conf, time = self.next_fit(weight, C)
print(c)
print(time)
c1 = str(c)
self.nbr_bin.setText(c1)
tex = time * 1000
tex1 = str(tex)
self.t_exe.setText(tex1)
print("nooo")
l = list_of_lists[0]
print(l)
g = str(l)
print("hi", g)
self.items_nb.setText(g)
r = str(C)
print("hi", g, r)
self.bin_cap.setText(r)