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permissibleLS.py
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permissibleLS.py
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from Params import configs
import numpy as np
def permissibleLeftShift(a, durMat, mchMat, mchsStartTimes, opIDsOnMchs):
jobRdyTime_a, mchRdyTime_a = calJobAndMchRdyTimeOfa(a, mchMat, durMat, mchsStartTimes, opIDsOnMchs)
dur_a = np.take(durMat, a)
mch_a = np.take(mchMat, a) - 1
startTimesForMchOfa = mchsStartTimes[mch_a]
opsIDsForMchOfa = opIDsOnMchs[mch_a]
flag = False
possiblePos = np.where(jobRdyTime_a < startTimesForMchOfa)[0]
# print('possiblePos:', possiblePos)
if len(possiblePos) == 0:
startTime_a = putInTheEnd(a, jobRdyTime_a, mchRdyTime_a, startTimesForMchOfa, opsIDsForMchOfa)
else:
idxLegalPos, legalPos, endTimesForPossiblePos = calLegalPos(dur_a, jobRdyTime_a, durMat, possiblePos, startTimesForMchOfa, opsIDsForMchOfa)
# print('legalPos:', legalPos)
if len(legalPos) == 0:
startTime_a = putInTheEnd(a, jobRdyTime_a, mchRdyTime_a, startTimesForMchOfa, opsIDsForMchOfa)
else:
flag = True
startTime_a = putInBetween(a, idxLegalPos, legalPos, endTimesForPossiblePos, startTimesForMchOfa, opsIDsForMchOfa)
return startTime_a, flag
def putInTheEnd(a, jobRdyTime_a, mchRdyTime_a, startTimesForMchOfa, opsIDsForMchOfa):
# index = first position of -config.high in startTimesForMchOfa
# print('Yes!OK!')
index = np.where(startTimesForMchOfa == -configs.high)[0][0]
startTime_a = max(jobRdyTime_a, mchRdyTime_a)
startTimesForMchOfa[index] = startTime_a
opsIDsForMchOfa[index] = a
return startTime_a
def calLegalPos(dur_a, jobRdyTime_a, durMat, possiblePos, startTimesForMchOfa, opsIDsForMchOfa):
startTimesOfPossiblePos = startTimesForMchOfa[possiblePos]
durOfPossiblePos = np.take(durMat, opsIDsForMchOfa[possiblePos])
startTimeEarlst = max(jobRdyTime_a, startTimesForMchOfa[possiblePos[0]-1] + np.take(durMat, [opsIDsForMchOfa[possiblePos[0]-1]]))
endTimesForPossiblePos = np.append(startTimeEarlst, (startTimesOfPossiblePos + durOfPossiblePos))[:-1]# end time for last ops don't care
possibleGaps = startTimesOfPossiblePos - endTimesForPossiblePos
idxLegalPos = np.where(dur_a <= possibleGaps)[0]
legalPos = np.take(possiblePos, idxLegalPos)
return idxLegalPos, legalPos, endTimesForPossiblePos
def putInBetween(a, idxLegalPos, legalPos, endTimesForPossiblePos, startTimesForMchOfa, opsIDsForMchOfa):
earlstIdx = idxLegalPos[0]
# print('idxLegalPos:', idxLegalPos)
earlstPos = legalPos[0]
startTime_a = endTimesForPossiblePos[earlstIdx]
# print('endTimesForPossiblePos:', endTimesForPossiblePos)
startTimesForMchOfa[:] = np.insert(startTimesForMchOfa, earlstPos, startTime_a)[:-1]
opsIDsForMchOfa[:] = np.insert(opsIDsForMchOfa, earlstPos, a)[:-1]
return startTime_a
def calJobAndMchRdyTimeOfa(a, mchMat, durMat, mchsStartTimes, opIDsOnMchs):
mch_a = np.take(mchMat, a) - 1
# cal jobRdyTime_a
jobPredecessor = a - 1 if a % mchMat.shape[1] != 0 else None
if jobPredecessor is not None:
durJobPredecessor = np.take(durMat, jobPredecessor)
mchJobPredecessor = np.take(mchMat, jobPredecessor) - 1
jobRdyTime_a = (mchsStartTimes[mchJobPredecessor][np.where(opIDsOnMchs[mchJobPredecessor] == jobPredecessor)] + durJobPredecessor).item()
else:
jobRdyTime_a = 0
# cal mchRdyTime_a
mchPredecessor = opIDsOnMchs[mch_a][np.where(opIDsOnMchs[mch_a] >= 0)][-1] if len(np.where(opIDsOnMchs[mch_a] >= 0)[0]) != 0 else None
if mchPredecessor is not None:
durMchPredecessor = np.take(durMat, mchPredecessor)
mchRdyTime_a = (mchsStartTimes[mch_a][np.where(mchsStartTimes[mch_a] >= 0)][-1] + durMchPredecessor).item()
else:
mchRdyTime_a = 0
return jobRdyTime_a, mchRdyTime_a
if __name__ == "__main__":
from JSSP_Env import SJSSP
from uniform_instance_gen import uni_instance_gen
import time
n_j = 3
n_m = 3
low = 1
high = 99
SEED = 10
np.random.seed(SEED)
env = SJSSP(n_j=n_j, n_m=n_m)
'''arr = np.ones(3)
idces = np.where(arr == -1)
print(len(idces[0]))'''
# rollout env random action
t1 = time.time()
data = uni_instance_gen(n_j=n_j, n_m=n_m, low=low, high=high)
print('Dur')
print(data[0])
print('Mach')
print(data[-1])
print()
# start time of operations on machines
mchsStartTimes = -configs.high * np.ones_like(data[0].transpose(), dtype=np.int32)
# Ops ID on machines
opIDsOnMchs = -n_j * np.ones_like(data[0].transpose(), dtype=np.int32)
# random rollout to test
# count = 0
_, _, omega, mask = env.reset(data)
rewards = []
flags = []
# ts = []
while True:
action = np.random.choice(omega[np.where(mask == 0)])
print(action)
mch_a = np.take(data[-1], action) - 1
# print(mch_a)
# print('action:', action)
# t3 = time.time()
adj, _, reward, done, omega, mask = env.step(action)
# t4 = time.time()
# ts.append(t4 - t3)
# jobRdyTime_a, mchRdyTime_a = calJobAndMchRdyTimeOfa(a=action, mchMat=data[-1], durMat=data[0], mchsStartTimes=mchsStartTimes, opIDsOnMchs=opIDsOnMchs)
# print('mchRdyTime_a:', mchRdyTime_a)
startTime_a, flag = permissibleLeftShift(a=action, durMat=data[0].astype(np.single), mchMat=data[-1], mchsStartTimes=mchsStartTimes, opIDsOnMchs=opIDsOnMchs)
flags.append(flag)
# print('startTime_a:', startTime_a)
# print('mchsStartTimes\n', mchsStartTimes)
# print('NOOOOOOOOOOOOO' if not np.array_equal(env.mchsStartTimes, mchsStartTimes) else '\n')
print('opIDsOnMchs\n', opIDsOnMchs)
# print('LBs\n', env.LBs)
rewards.append(reward)
# print('ET after action:\n', env.LBs)
print()
if env.done():
break
t2 = time.time()
print(t2 - t1)
# print(sum(ts))
# print(np.sum(opIDsOnMchs // n_m, axis=1))
# print(np.where(mchsStartTimes == mchsStartTimes.max()))
# print(opIDsOnMchs[np.where(mchsStartTimes == mchsStartTimes.max())])
print(mchsStartTimes.max() + np.take(data[0], opIDsOnMchs[np.where(mchsStartTimes == mchsStartTimes.max())]))
# np.save('sol', opIDsOnMchs // n_m)
# np.save('jobSequence', opIDsOnMchs)
# np.save('testData', data)
# print(mchsStartTimes)
durAlongMchs = np.take(data[0], opIDsOnMchs)
mchsEndTimes = mchsStartTimes + durAlongMchs
print(mchsStartTimes)
print(mchsEndTimes)
print()
print(env.opIDsOnMchs)
print(env.adj)
# print(sum(flags))
# data = np.load('data.npy')
# print(len(np.where(np.array(rewards) == 0)[0]))
# print(rewards)