def first_fit_dec(list_items, max_size): """ Returns list of bins with input items inside. """ # Sort list in decreasing order list_items.sort(reverse=True) # Apply first-fit algorith return(first_fit(list_items, max_size))
def first_fit_dec(list_items, max_size):
""" Returns list of bins with input items inside. """
# Sort list in decreasing order
list_items.sort(reverse=True)
# Apply first-fit algorith
return (first_fit(list_items, max_size))
state = sim.simxUnpackFloats(data)
state = np.array(state)
state = state.reshape((120, -1))
r, dim = sim.simxGetStringSignal(clientID, 'DIM',
sim.simx_opmode_blocking)
dim = sim.simxUnpackFloats(dim)
if (boxes_generated == 0):
boxes_generated = int(dim[3])
dim = dim[0:3]
#print(dim)
sim.simxSetStringSignal(clientID, 'STATE', '',
sim.simx_opmode_oneshot)
if heuristics == 'walle':
pos = np.array(walle(state, dim))
if heuristics == 'first_fit':
pos = np.array(first_fit(state, dim))
if heuristics == 'floor_building':
pos = np.array(floor_building(state, dim))
# pos=np.array(column_building(state,dim))
send_pos = sim.simxPackInts(pos)
#print(send_pos)
if dim[0] < 10 or dim[1] < 10 or dim[2] < 10:
sim.simxStopSimulation(clientID, sim.simx_opmode_oneshot)
# sim.simxpauseSimulation(clientID,sim.simx_opmode_oneshot)
break
sim.simxSetStringSignal(clientID, 'POSFOUND', send_pos,
sim.simx_opmode_oneshot)
if (pos[0] > 0):
boxesVolumesSum += dim[0] * dim[1] * dim[2]
num += 1
patience = 0
# Examples from first_fit import first_fit from first_fit_dec import first_fit_dec items = [8, 16, 12, 8, 45, 18, 30, 7, 10, 14, 9, 9, 52, 88] bin_height = 60 # First-fit Algorithm print(first_fit(items, bin_height)) # First-fit Decreasing Algorithm print(first_fit_dec(items, bin_height))
import csv
import numpy as np
from first_fit import first_fit
inputFile = open("bpp_instances.txt", "r")
for line in inputFile:
data = np.array(line.split(","), dtype=np.int32)
print(first_fit(data[1:], data[0]))
inputFile.close()
