def assignNurses(solution, hini, data):
"""
hini is used as the highest hour at which a nuser can start working.
If at hini a nuses has not started working, that nuser won't work.
A nurse can work before hini,(if there is enough demand)
"""
demand = data["demand"]
pending = solution["pending"]
hours = data["hours"]
sumW = [0] * data["nNurses"]
z = solution["z"]
w = solution["w"]
for h in range(hours):
# for each hour
# compute valid candidates
# those who must be assigned (rest constraint)
# those who can be assigned to work
# if h>hini and z[n]== 0 , that nurse cannot work
mustWork, canWork = computeAssignments(solution, h, data, sumW, hini)
# print("h=" + str(h))
# print("mustWork")
# print(mustWork)
# print("canWork")
# print(canWork)
# print("hini:")
# print(hini)
# print("demand")
# print(data["demand"])
# print("pending")
# print(solution["pending"])
# try to assign if pending[h] > 0 and h >= hini[n]
for n in mustWork:
# print("nurse :" + str(n) + " h: " + str(h) + " pending: ")
# print(pending)
w[n][h] = 1
sumW[n] += 1
pending[h] -= 1
if z[n] == 0:
z[n] = 1
solution["cost"] += 1
#print("w[" + str(n) + "," + str(h) + "] = 1")
# pp.pprint(solution["w"])
for n in canWork:
# print("nurse :" + str(n) + " h: " + str(h) + " pending: ")
# print(pending)
if pending[h] > 0:
w[n][h] = 1
sumW[n] += 1
pending[h] -= 1
if z[n] == 0:
z[n] = 1
solution["cost"] += 1
#print("w[" + str(n) + "," + str(h) + "] = 1")
# print("w[" + str(n) + "]")
# pp.pprint(solution["w"])
# if pending[h] > 0:
# print(" h:" + str(h) + " pending[h]=" + str(pending[h]))
# print(solution["pending"])
# print("")
# pp.pprint(data)
# pp.pprint(solution["cost"])
# exit()
# compute cost: already updated!
# compute feasibility: if unfeasible -> fitness should be inf
if not isFeasible(solution, data):
# assign the max cost
solution["cost"] = 200000 * data["nNurses"]
def assignNurses(solution, hini, data):
"""
hini is used to add extra nurses at each hour
hini[h]=0.2 -> means we add 0.1*demand[h] in terms of nurse assigments
"""
demand = data["demand"]
pending = solution["pending"]
hours = data["hours"]
sumW = [0] * data["nNurses"]
z = solution["z"]
w = solution["w"]
for h in range(hours):
# for each hour
# compute valid candidates
# those who must be assigned (rest constraint)
# those who can be assigned to work
# if h>hini and z[n]== 0 , that nurse cannot work
mustWork, canWork = computeAssignments(solution, h, data, sumW)
# print("h=" + str(h))
# print("mustWork")
# print(mustWork)
# print("canWork")
# print(canWork)
# print("hini:")
# print(hini)
# print("demand")
# print(data["demand"])
# print("pending")
# print(solution["pending"])
# try to assign if pending[h] > 0 and h >= hini[n]
for n in mustWork:
# print("nurse :" + str(n) + " h: " + str(h) + " pending: ")
# print(pending)
w[n][h] = 1
sumW[n] += 1
pending[h] -= 1
if z[n] == 0:
z[n] = 1
solution["cost"] += 1
#print("w[" + str(n) + "," + str(h) + "] = 1")
# pp.pprint(solution["w"])
for n in canWork:
# print("nurse :" + str(n) + " h: " + str(h) + " pending: ")
# print(pending)
if pending[h] + hini[h] > 0:
w[n][h] = 1
sumW[n] += 1
pending[h] -= 1
if z[n] == 0:
z[n] = 1
solution["cost"] += 1
#print("w[" + str(n) + "," + str(h) + "] = 1")
# print("w[" + str(n) + "]")
# pp.pprint(solution["w"])
# pp.pprint(data)
# pp.pprint(solution["cost"])
# exit()
# compute feasibility: if unfeasible -> fitness should be inf
if not isFeasible(solution, data):
# assign the max cost
solution["cost"] = 200000 * data["nNurses"]
def assignNurses(solution, hini, data):
"""
hini is used to add extra nurses at each hour
hini[h]=0.2 -> means we add 0.1*demand[h] in terms of nurse assigments
"""
demand = data["demand"]
pending = solution["pending"]
hours = data["hours"]
sumW = [0] * data["nNurses"]
checkers = initCheckers(data)
z = solution["z"]
w = solution["w"]
for h in range(hours):
#print(" for loop h="+str(h))
solution["mustWork_count"] = 0
mustWork, canWork = computeAssignments(solution,
h,
data,
checkers=checkers,
sumW=sumW)
# print("h=" + str(h))
# print("mustWork")
# print(mustWork)
# print("canWork")
# print(canWork)
# print("hini:")
# print(hini)
# print("demand")
# print(data["demand"])
# print("pending")
# print(solution["pending"])
# try to assign if pending[h] > 0 and h >= hini[n]
for n in mustWork:
# print("nurse :" + str(n) + " h: " + str(h) + " pending: ")
# print(pending)
update_checkers(solution, data, n, h, 1, checkers)
w[n][h] = 1
sumW[n] += 1
pending[h] -= 1
if z[n] == 0:
z[n] = 1
solution["cost"] += 1
#print("w[" + str(n) + "," + str(h) + "] = 1")
# pp.pprint(solution["w"])
for n in canWork:
# print("nurse :" + str(n) + " h: " + str(h) + " pending: ")
# print(pending)
if pending[h] + hini[h] > 0:
update_checkers(solution, data, n, h, 1, checkers)
w[n][h] = 1
sumW[n] += 1
pending[h] -= 1
if z[n] == 0:
z[n] = 1
solution["cost"] += 1
#print("w[" + str(n) + "," + str(h) + "] = 1")
# print("w[" + str(n) + "]")
# pp.pprint(solution["w"])
# pp.pprint(data)
# pp.pprint(solution["cost"])
# print("")
# compute feasibility: if unfeasible -> fitness should be inf
if not isFeasible(solution, data):
# assign the max cost
#solution["cost"] = 200000 * data["nNurses"]
solution["cost"] = 100 * solution["cost"]