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Commit 19ebcccd authored by Goes,M. (Martijn)'s avatar Goes,M. (Martijn)
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fix: some constraints, more to do

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__pycache__/offline.cpython-310.pyc
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offline.py
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......@@ -32,6 +32,7 @@ def Solve(images, blackouts):
"""PARAMETERS"""
h = GRB.INFINITY # time horizon = infinite
tfU_j = GRB.INFINITY
# YA_t_br = [] # both not used
# YB_t_br = []
......@@ -39,10 +40,10 @@ def Solve(images, blackouts):
""""DECISION VARIABLES"""
# makespan
ms = model.addVar(lb=0,vtype=GRB.CONTINUOUS) # makespan, objective function minimization value, bounded with constraints
P_j_br = model.addVars(image_count, blackout_count,lb=0,vtype=GRB.CONTINUOUS) # preemption time, will be set to 0 in Eq (33)
# P_j_br = model.addVars(image_count, blackout_count,lb=0,vtype=GRB.CONTINUOUS) # preemption time, will be set to 0 in Eq (33)
PV_t = model.addVars(whitebox_count,lb=0,vtype=GRB.CONTINUOUS) # sum of length of images in whitebox t
Tf_j = model.addVars(image_count,lb=0,vtype=GRB.CONTINUOUS) # finish of image j
Tf_t = model.addVars(whitebox_count,lb=0,vtype=GRB.CONTINUOUS) # finish of all images is whitebox t
Tf_t = model.addVars(whitebox_count,lb=0,vtype=GRB.CONTINUOUS) # finish of all images in whitebox t
Ts_j = model.addVars(image_count,lb=0,vtype=GRB.CONTINUOUS) # start of image j
Ts_t = model.addVars(whitebox_count,lb=0,vtype=GRB.CONTINUOUS) # start of timeslot t, probably redundant
X_j_t = model.addVars(image_count, whitebox_count,vtype=GRB.BINARY) # order j in whitebox t
......@@ -52,6 +53,10 @@ def Solve(images, blackouts):
YB_j_br = model.addVars(image_count, blackout_count,vtype=GRB.BINARY) # order j finishes before blackbox br
"""CONSTRAINTS"""
# model.addConstr(Y_j_jprime[0,0] == 0)
# model.addConstr(Y_j_jprime[0,1] == 0)
# model.addConstr(Y_j_jprime[1,0] == 1)
# model.addConstr(Y_j_jprime[1,1] == 0)
# (1) minimize makespan
model.setObjective(ms, GRB.MINIMIZE)
# (3)
......@@ -63,6 +68,21 @@ def Solve(images, blackouts):
for j in range(image_count)
for jprime in range(image_count)),
name="Eq(4)")
# (4 v2)
# model.addConstrs((Tf_j[j] <= Ts_j[jprime] + tfU_j * (1 - Y_j_jprime[j,jprime])
# for j in range(image_count)
# for jprime in range(image_count)),
# name="Eq(4 v2)")
# (4 v3)
# for j in range(image_count):
# for jprime in range(j+1,image_count):
# model.addConstr((Tf_j[j] <= Ts_j[jprime] + tfU_j * (1 - Y_j_jprime[j,jprime])),
# name="Eq(4 v2)")
# # (5 v3)
# for j in range(image_count):
# for jprime in range(j+1,image_count):
# model.addConstr((Tf_j[jprime] <= Ts_j[j] + tfU_j * (1 + Y_j_jprime[j,jprime])),
# name="Eq(5 v3)")
# (9)
model.addConstrs((ms >= Tf_j[j]
for j in range(image_count)),
......@@ -77,7 +97,8 @@ def Solve(images, blackouts):
name="Eq(13)")
# (17)
model.addConstrs((gp.quicksum(X_j_t[j,t] for j in range(image_count))
+ Xfree_t[t] == 1
+ Xfree_t[t]
== 1
for t in range(whitebox_count)),
name="Eq(17)")
# (19)
......@@ -91,15 +112,15 @@ def Solve(images, blackouts):
for t in range(whitebox_count)),
name="Eq(20)")
# (32)
model.addConstrs((YB_j_br[j,br_index] + YA_j_br[j,br_index] == X_j_t[j,t]
for j in range(image_count)
for t in range (whitebox_count)
for br_index in range(blackout_count)),
name="Eq(32)")
# model.addConstrs((YB_j_br[j,br_index] + YA_j_br[j,br_index] == X_j_t[j,t]
# for j in range(image_count)
# for t in range (whitebox_count)
# for br_index in range(blackout_count)),
# name="Eq(32)")
# (33)
model.addConstrs((P_j_br[j,br_index] == 0 for j in range(image_count)
for br_index in range(blackout_count)),
name="Eq(33)")
# model.addConstrs((P_j_br[j,br_index] == 0 for j in range(image_count)
# for br_index in range(blackout_count)),
# name="Eq(33)")
# (34)
model.addConstrs((br[br_index][1] * YA_j_br[j,br_index] <= Ts_j[j]
for br_index in range(blackout_count)
......@@ -124,36 +145,47 @@ def Solve(images, blackouts):
# SOLVE AND PRINT THE RESULTS
model.optimize()
res = printSolution(model)
return (res[0], res[1])
time = -1
starts = [-1]
if model.status == GRB.OPTIMAL:
deletus = starts.pop()
time = model.ObjVal
print('\nFinish time: %g' % time)
print("White box decision variables:")
for (j,t) in X_j_t:
print(f"(im{j},wb{t}) = {X_j_t[j,t].X}")
print('\nTimes:')
for im in Ts_j:
ts = Ts_j[im].X
tf = Tf_j[im].X
print(f"Image {im} starts t={ts} finishes t={tf}")
starts.append(t)
print('\nOrder:')
for im in Ts_j:
for im2 in Ts_j:
print(f"{im} before {im2}: {Y_j_jprime[im, im2].X}")
print('\nWhitebox contains:')
for t in PV_t:
print(f"wb{t} is {Xfree_t[t].X} empty and holds length {PV_t[t].X} of images")
print('\nBlackboxes before/after:')
for (j,br_index) in YA_j_br:
print(f"YA_{j}_{br_index}: image {j} after blackbox {br_index} = {YA_j_br[j,br_index].X}")
print(f"YB_{j}_{br_index}: image {j} before blackbox {br_index} = {YB_j_br[j,br_index].X}")
def printSolution(model):
if model.status == GRB.OPTIMAL:
print('\nFinish time: %g' % model.ObjVal)
else:
print('\nNo solution, reason:')
iis = model.computeIIS() # Irreducible Infeasible Subsystem, https://support.gurobi.com/hc/en-us/articles/360029969391-How-do-I-determine-why-my-model-is-infeasible-
print(iis)
# time = None
# timeSteps = []
# if model.status == GRB.OPTIMAL:
# time = None
# # TODO: loop over decision variables
# # i.e. for all images in whitebox j:
# # their order does not matter
# # so just paste them behind each other
# # timeSteps.append(decVariables[x_ij].X)
# # timeSteps.append(1234)
# else:
# time = "No solution"
# return (41.618, [35, 29.6, 18, 35.618, 0.86]) # answer to test instance 0
return (45, [22, 4, 35, 42, 0, 5, 28, 11]) # answer to test instance 1
# return (time, timeSteps)
# return (45, [22, 4, 35, 42, 0, 5, 28, 11]) # answer to test instance 1
return (time, starts)
def calculate_whiteboxes(blackouts):
wb = []
......
t4_in.txt
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......@@ -2,4 +2,4 @@
10
15
1
50, 10
\ No newline at end of file
25, 5
\ No newline at end of file
t4_out.txt
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− 9
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45
22
4
35
42
0
5
28
11
\ No newline at end of file
15.0
1
1
\ No newline at end of file
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