No solution found when using an objective function
Answered
Hi,
I have an MIP which consists of roughly 3 000 000 binary variables before presolve (2 000 000 after presolve).
The goal is to generate timetables according to constraints.
My decision variables array is a 4D array whose dimensions are :
- days
- time slots
- rooms
- sessions
When i don't use an objective function, I am able to find a feasible solution in less than 20-25 minutes ; however, when I try to use an objective function, the optimization just goes on forever and will eventually show warning messages such as :
Warning: 1 variables dropped from basis
Warning: switch to quad precision
or
Warning : Markowitz tolerance tightened
Do you have any idea on how to get a suboptimal solution in decent time (less than 1 hour) ?
Do i have to reformulate my whole model to try and make it smaller ?
Thank you all for your kind help,
Matthieu
P.S : I put the code below in case you would like to check it but you don't necessarily need to read it.
# DECISION VARIABLES ARRAY INITIALIZATION
decision_vars = day_room_time_model.addVars(number_of_days,
int(shifts_per_day),rooms.__len__(),
current_week_sessions.__len__(), vtype=GRB.BINARY)
# VARIABLES USED IN OBJECTIVE FUNCTION
saturday_sessions =
quicksum(decision_vars[5, sh, r, se.week_array_index]
for sh in range(shifts_per_day) for r in range(rooms.__len__())
for se in current_week_sessions)
evening_sessions =
quicksum(decision_vars[d, sh, r, se.week_array_index]
for d in range(number_of_days)
for sh in range(9 * shifts_per_hour, shifts_per_day)
for r in range(rooms.__len__())
for se in current_week_sessions)
room_optimization = quicksum(
decision_vars[d, sh, r.main_array_index, se.week_array_index]
* (r.capacity - se.students.__len__())
for d in range(number_of_days)
for sh in range(shifts_per_day)
for r in rooms
for se in current_week_sessions)
# OBJECTIVE FUNCTION DEFINITION
day_room_time_model.setObjective(evening_sessions +
room_optimization + saturday_sessions ,GRB.MINIMIZE)
# CONSTRAINT : NUMBER OF STUDENTS INFERIOR TO ROOM SIZE CONSTRAINT
for r in rooms:
for se in current_week_sessions:
if r.capacity < se.students.__len__():
for d in range(number_of_days):
for sh in range(shifts_per_day):
decision_vars[d, sh, r.main_array_index, se.week_array_index].UB = 0
decision_vars[d, sh, r.main_array_index, se.week_array_index].LB = 0
# CONSTRAINT : A SESSION HAS TO BE ASSIGNED ONCE AND ONLY ONCE CONSTRAINT
day_room_time_model.addConstrs(
(decision_vars.sum('*', '*', '*', session.week_array_index)
== session.course.number_of_shifts
for session in current_week_sessions),
name="SESSION HAS TO BE ASSIGNED/")
# CONSTRAINT : SHIFTS OF A SESSIONS MUST BE CONSECUTIVE
day_room_time_model.addConstrs(
(decision_vars[d, sh, r, session.week_array_index] >=
(decision_vars[d, sh - 1, r, session.week_array_index] -
((1 / session.course.number_of_shifts) *
decision_vars.sum(
d,
range(max(0, sh - session.course.number_of_shifts),sh),
r,
session.week_array_index)))
for session in current_week_sessions
for d in range(number_of_days)
for r in range(rooms.__len__())
for sh in range(1, int(shifts_per_day))),
name="CONSECUTIVE SHIFTS/")
# CONSTRAINT : SHIFTS ALL SAME DAY AND SAME ROOM
day_room_time_model.addConstrs(
(decision_vars[d, sh, r, session.week_array_index] -
decision_vars[d, sh - 1, r, session.week_array_index] == 0
for session in current_week_sessions
for sh in range(shifts_per_day - session.course.number_of_shifts + 1, shifts_per_day)
for d in range(number_of_days)
for r in range(rooms.__len__())),
name="SHIFTS ALL SAME DAY AND SAME ROOM/")
# CONSTRAINT : ONLY ONE SESSION AT A TIME PER ROOM
day_room_time_model.addConstrs(
(decision_vars.sum(d, sh, r, '*') <= 1
for d in range(number_of_days)
for sh in range(shifts_per_day)
for r in range(rooms.__len__())),
name="ONE SESSION PER ROOM/")
# CONSTRAINT : NO OVERLAP BETWEEN TEACHER COURSES
for teacher in teachers.values():
teacher_week_sessions = teacher.week_sessions[current_week_index]
if (teacher_week_sessions != []):
day_room_time_model.addConstrs(
(decision_vars.sum(d, sh, '*', teacher_week_sessions) <= 1
for d in range(number_of_days)
for sh in range(shifts_per_day)),
name="TEACH NO OVERLAP/")
# CONSTRAINT : MINIMUM LUNCH TIME
day_room_time_model.addConstrs(
decision_vars.sum(d,
range(minimum_lunch_time_shift,maximum_lunch_time_shift + 1),
'*',teacher_week_sessions) <= (maximum_lunch_time_shift -
minimum_lunch_time_shift + 1) - number_time_shifts_for_lunch
for d in range(number_of_days))
# NO OVERLAP BETWEEN STUDENTS' COURSES
for student in students.values():
student_week_sessions = student.week_sessions[current_week_index]
if (student_week_sessions != []):
day_room_time_model.addConstrs((
decision_vars.sum(d, sh, '*', student_week_sessions)
<= 1 for d in range(number_of_days)
for sh in range(shifts_per_day)),
name="STUDENT NO OVERLAP/")
# CONSTRAINT : MINIMUM LUNCH TIME
day_room_time_model.addConstrs(
decision_vars.sum(d, range(minimum_lunch_time_shift,
maximum_lunch_time_shift + 1), '*',student_week_sessions)
<= (maximum_lunch_time_shift - minimum_lunch_time_shift + 1)
- number_time_shifts_for_lunch
for d in range(number_of_days))
# SOLVING PARAMETERS
day_room_time_model.setParam(GRB.Param.Threads, 3) # TRIED MORE (16 MAX) BUT IT CRASHES WITH BARRIER
day_room_time_model.setParam(GRB.Param.Method, 2) # TRIED PRIMAL SIMPLEX BUT DOESN'T CONVERGE EITHER
day_room_time_model.setParam(GRB.Param.Presolve, 0) # TRIED WITH DEFAULT AND 2
day_room_time_model.setParam(GRB.Param.MIPFocus, 1)
day_room_time_model.setParam(GRB.Param.ImproveStartTime, 1800)
day_room_time_model.setParam(GRB.Param.SolutionLimit, 1)
# SOLVE MODEL
day_room_time_model.optimize()
-
Official comment
This post is more than three years old. Some information may not be up to date. For current information, please check the Gurobi Documentation or Knowledge Base. If you need more help, please create a new post in the community forum. Or why not try our AI Gurobot?. -
What parameters are you using? Would you please post your log file?
0 -
Parameters I tried are :
day_room_time_model.setParam(GRB.Param.Threads, 3) # TRIED MORE (16 MAX) BUT IT CRASHES WITH BARRIER
day_room_time_model.setParam(GRB.Param.Method, 2) # TRIED PRIMAL SIMPLEX AND DUAL BUT DOESN'T CONVERGE EITHER
day_room_time_model.setParam(GRB.Param.Presolve, 0) # TRIED WITH DEFAULT AND 2
day_room_time_model.setParam(GRB.Param.MIPFocus, 1)
day_room_time_model.setParam(GRB.Param.ImproveStartTime, 1800)
day_room_time_model.setParam(GRB.Param.SolutionLimit, 1)I'll post the log file soon
0 -
Changed value of parameter Threads to 16
Prev: 0 Min: 0 Max: 1024 Default: 0
weeks model is being solved
Gurobi Optimizer version 9.0.0 build v9.0.0rc2 (win64)
Optimize a model with 2506 rows, 443 columns and 12440 nonzeros
Model fingerprint: 0x87634e85
Variable types: 0 continuous, 443 integer (443 binary)
Coefficient statistics:
Matrix range [1e+00, 9e+00]
Objective range [0e+00, 0e+00]
Bounds range [1e+00, 1e+00]
RHS range [1e+00, 9e+01]
Found heuristic solution: objective 0.0000000Explored 0 nodes (0 simplex iterations) in 0.02 seconds
Thread count was 1 (of 16 available processors)Solution count 1: 0
Optimal solution found (tolerance 1.00e-04)
Best objective 0.000000000000e+00, best bound 0.000000000000e+00, gap 0.0000%
Obj: 0WEEK #0 IS BEING SOLVED
number of sessions :443
Milestone 1
Milestone 2
Milestone 3
Milestone 4
Milestone 5
Milestone 6
MODEL IS BUILT
Changed value of parameter Threads to 3
Prev: 0 Min: 0 Max: 1024 Default: 0
Changed value of parameter Method to 2
Prev: -1 Min: -1 Max: 5 Default: -1
Changed value of parameter Presolve to 2
Prev: -1 Min: -1 Max: 2 Default: -1
Changed value of parameter MIPFocus to 1
Prev: 0 Min: 0 Max: 3 Default: 0
Changed value of parameter ImproveStartTime to 1800.0
Prev: inf Min: 0.0 Max: inf Default: inf
Changed value of parameter SolutionLimit to 1
Prev: 2000000000 Min: 1 Max: 2000000000 Default: 2000000000
Gurobi Optimizer version 9.0.0 build v9.0.0rc2 (win64)
Optimize a model with 3487757 rows, 2998224 columns and 125843346 nonzeros
Model fingerprint: 0x9172f33a
Variable types: 0 continuous, 2998224 integer (2998224 binary)
Coefficient statistics:
Matrix range [1e-01, 1e+00]
Objective range [1e+00, 2e+02]
Bounds range [1e+00, 1e+00]
RHS range [1e+00, 9e+00]
Presolve removed 0 rows and 0 columns (presolve time = 10s) ...
Presolve removed 801648 rows and 730800 columns (presolve time = 15s) ...
Presolve removed 1106436 rows and 1035588 columns (presolve time = 22s) ...
Presolve removed 1411224 rows and 1035588 columns (presolve time = 26s) ...
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Presolve removed 1505645 rows and 1035598 columns
Presolve time: 1343.35s
Presolved: 1982112 rows, 1962626 columns, 52960894 nonzeros
Variable types: 0 continuous, 1962626 integer (1962626 binary)
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Presolve removed 304 rows and 3 columns
Presolved: 1981808 rows, 1962623 columns, 52861009 nonzerosRoot barrier log...
Elapsed ordering time = 5s
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Elapsed ordering time = 35s
Elapsed ordering time = 40s
Elapsed ordering time = 45s
Elapsed ordering time = 50s
Elapsed ordering time = 55s
Elapsed ordering time = 60s
Elapsed ordering time = 65s
Elapsed ordering time = 70s
Elapsed ordering time = 75s
Elapsed ordering time = 80s
Elapsed ordering time = 85s
Elapsed ordering time = 90s
Elapsed ordering time = 95s
Elapsed ordering time = 100s
Elapsed ordering time = 105s
Elapsed ordering time = 110s
Elapsed ordering time = 115s
Elapsed ordering time = 120s
Elapsed ordering time = 125s
Elapsed ordering time = 130s
Elapsed ordering time = 135s
Elapsed ordering time = 140s
Elapsed ordering time = 145s
Elapsed ordering time = 150s
Elapsed ordering time = 155s
Elapsed ordering time = 160s
Elapsed ordering time = 165s
Elapsed ordering time = 170s
Elapsed ordering time = 175s
Elapsed ordering time = 180s
Elapsed ordering time = 185s
Elapsed ordering time = 190s
Elapsed ordering time = 195s
Elapsed ordering time = 200s
Elapsed ordering time = 205s
Elapsed ordering time = 210s
Elapsed ordering time = 215s
Elapsed ordering time = 319s
Elapsed ordering time = 320s
Elapsed ordering time = 325s
Elapsed ordering time = 330s
Elapsed ordering time = 335s
Elapsed ordering time = 340s
Elapsed ordering time = 345s
Elapsed ordering time = 350s
Elapsed ordering time = 355s
Elapsed ordering time = 360s
Elapsed ordering time = 365s
Elapsed ordering time = 370s
Elapsed ordering time = 375s
Elapsed ordering time = 380s
Elapsed ordering time = 385s
Elapsed ordering time = 390s
Elapsed ordering time = 395s
Elapsed ordering time = 400s
Elapsed ordering time = 405s
Elapsed ordering time = 410s
Elapsed ordering time = 415s
Elapsed ordering time = 420s
Elapsed ordering time = 425s
Elapsed ordering time = 430s
Elapsed ordering time = 435s
Elapsed ordering time = 440s
Elapsed ordering time = 445s
Elapsed ordering time = 450s
Elapsed ordering time = 455s
Elapsed ordering time = 460s
Elapsed ordering time = 465s
Elapsed ordering time = 470s
Elapsed ordering time = 475s
Elapsed ordering time = 480s
Elapsed ordering time = 485s
Elapsed ordering time = 490s
Elapsed ordering time = 495s
Elapsed ordering time = 500s
Elapsed ordering time = 505s
Elapsed ordering time = 510s
Elapsed ordering time = 515s
Elapsed ordering time = 520s
Elapsed ordering time = 525s
Elapsed ordering time = 530s
Elapsed ordering time = 535s
Elapsed ordering time = 540s
Elapsed ordering time = 545s
Elapsed ordering time = 550s
Elapsed ordering time = 555s
Ordering time: 612.08sBarrier statistics:
AA' NZ : 1.896e+08
Factor NZ : 8.566e+08 (roughly 9.0 GBytes of memory)
Factor Ops : 2.610e+12 (roughly 120 seconds per iteration)
Threads : 3Objective Residual
Iter Primal Dual Primal Dual Compl Time
0 1.25804843e+09 0.00000000e+00 7.82e+04 0.00e+00 1.12e+03 2204s
1 1.09582463e+09 -8.84328591e+05 6.81e+04 8.68e+01 9.76e+02 2307s
2 7.10105476e+08 -2.46274393e+06 4.42e+04 5.18e+01 6.37e+02 2412s
3 3.81452187e+08 -3.90663177e+06 2.38e+04 2.10e+01 3.45e+02 2517s
4 1.24452432e+08 -4.39857604e+06 7.76e+03 6.37e+00 1.15e+02 2623s
5 6.26459082e+07 -3.79352778e+06 3.91e+03 2.91e+00 5.85e+01 2727s
6 1.40693023e+07 -2.67848171e+06 8.81e+02 6.37e-01 1.35e+01 2835s
7 3.34105481e+06 -1.65327462e+06 2.14e+02 2.57e-01 3.52e+00 2943s
8 1.48595860e+06 -1.01051545e+06 9.68e+01 1.13e-01 1.66e+00 3053s
9 6.53123458e+05 -7.32481202e+05 4.29e+01 6.73e-02 7.87e-01 3162s
10 3.23897481e+05 -5.13505052e+05 2.10e+01 5.55e-02 4.11e-01 3276s
11 1.51519340e+05 -3.53495171e+05 8.69e+00 2.69e-02 1.92e-01 3386s
12 4.02412521e+04 -1.46933758e+05 3.12e-01 4.55e-13 3.47e-02 3500s
13 2.39617474e+04 -9.50202362e+03 5.57e-14 4.55e-13 5.67e-03 3609s
14 1.46100442e+04 -1.41598014e+03 3.60e-14 4.55e-13 2.72e-03 3721s
15 1.19750707e+04 5.03956658e+02 3.13e-14 4.55e-13 1.94e-03 3829s
16 1.03803627e+04 1.50057652e+03 1.59e-13 4.55e-13 1.50e-03 3938s
17 9.24688496e+03 2.06882084e+03 8.30e-14 5.12e-13 1.22e-03 4046s
18 7.88213658e+03 2.43014201e+03 1.05e-13 2.27e-13 9.24e-04 4153s
19 7.40068969e+03 2.60325728e+03 1.07e-13 2.84e-13 8.13e-04 4262s
20 6.92514104e+03 2.78948732e+03 1.75e-13 2.27e-13 7.01e-04 4370s
21 6.42242404e+03 2.84534214e+03 1.51e-13 6.82e-13 6.06e-04 4475s
22 6.02560869e+03 2.95631317e+03 1.31e-13 2.27e-13 5.20e-04 4580s
23 5.16406141e+03 3.08543884e+03 4.47e-13 3.98e-13 3.52e-04 4685s
24 4.78383777e+03 3.26339784e+03 4.68e-13 6.25e-13 2.58e-04 4790s
25 4.24545529e+03 3.33200373e+03 1.42e-13 3.41e-13 1.55e-04 4896s
26 4.11792201e+03 3.35963419e+03 2.14e-13 2.84e-13 1.28e-04 5000s
27 3.93091387e+03 3.40116608e+03 3.31e-12 2.84e-13 8.97e-05 5105s
28 3.60274915e+03 3.40505733e+03 9.29e-12 3.41e-13 3.35e-05 5209s
29 3.50229263e+03 3.41542493e+03 4.05e-12 4.55e-13 1.47e-05 5318s
30 3.41712113e+03 3.41585875e+03 5.66e-13 6.82e-13 2.14e-07 5425s
31 3.41600112e+03 3.41599986e+03 7.06e-13 4.55e-13 2.14e-10 5529s
32 3.41600000e+03 3.41600000e+03 6.76e-13 7.67e-13 2.14e-13 5634sBarrier solved model in 32 iterations and 5633.68 seconds
Optimal objective 3.41600000e+03
Root crossover log...1659251 DPushes remaining with DInf 0.0000000e+00 5637s
0 DPushes remaining with DInf 2.9844238e-11 5640s197143 PPushes remaining with PInf 0.0000000e+00 5640s
165022 PPushes remaining with PInf 0.0000000e+00 5645s
155165 PPushes remaining with PInf 0.0000000e+00 5650s
Warning: 7 variables dropped from basisRestart crossover...
526546 variables added to crossover basis 5656s
1659251 DPushes remaining with DInf 0.0000000e+00 5657s
0 DPushes remaining with DInf 3.0009661e-11 5660s197143 PPushes remaining with PInf 0.0000000e+00 5660s
193181 PPushes remaining with PInf 0.0000000e+00 5660s
168420 PPushes remaining with PInf 0.0000000e+00 5665s
157717 PPushes remaining with PInf 0.0000000e+00 5671s
149966 PPushes remaining with PInf 0.0000000e+00 5675s
144093 PPushes remaining with PInf 0.0000000e+00 5680s
138341 PPushes remaining with PInf 0.0000000e+00 5685s
133700 PPushes remaining with PInf 0.0000000e+00 5691s
129822 PPushes remaining with PInf 0.0000000e+00 5696s
125610 PPushes remaining with PInf 0.0000000e+00 5701s
Warning: 1 variables dropped from basis
Warning: 3 variables dropped from basis
122249 PPushes remaining with PInf 5.2420380e+03 5706s
118925 PPushes remaining with PInf 4.8913941e+03 5711s
Warning: 7 variables dropped from basis
116744 PPushes remaining with PInf 4.4216688e+05 5715s
113669 PPushes remaining with PInf 3.9654323e+05 5721s
111175 PPushes remaining with PInf 3.8834244e+05 5726s
108682 PPushes remaining with PInf 3.7561739e+05 5731s
106257 PPushes remaining with PInf 3.7115870e+05 5736s
104823 PPushes remaining with PInf 3.6443637e+05 5741s
102457 PPushes remaining with PInf 3.6090892e+05 5746s
100210 PPushes remaining with PInf 3.5799665e+05 5751s
98809 PPushes remaining with PInf 3.5508056e+05 5756s
Warning: 2 variables dropped from basis
97285 PPushes remaining with PInf 3.5415041e+05 5760s
95010 PPushes remaining with PInf 3.5277600e+05 5766s
93603 PPushes remaining with PInf 3.5070119e+05 5770s
92013 PPushes remaining with PInf 3.4740441e+05 5775s
89778 PPushes remaining with PInf 3.4634509e+05 5781s
88313 PPushes remaining with PInf 3.4457436e+05 5785s
86730 PPushes remaining with PInf 3.4216557e+05 5791s
85204 PPushes remaining with PInf 3.4153815e+05 5795s
83027 PPushes remaining with PInf 3.4051651e+05 5803s
Warning: 5 variables dropped from basis
82322 PPushes remaining with PInf 7.9436171e+05 5806s
80749 PPushes remaining with PInf 7.8272085e+05 5812s
79207 PPushes remaining with PInf 7.8113538e+05 5817s
78444 PPushes remaining with PInf 7.7982090e+05 5820s
76956 PPushes remaining with PInf 7.7528665e+05 5826s
75525 PPushes remaining with PInf 7.7058160e+05 5833s
74658 PPushes remaining with PInf 7.6686407e+05 5836s
73118 PPushes remaining with PInf 7.6548810e+05 5841s
71663 PPushes remaining with PInf 7.6140522e+05 5847s
70974 PPushes remaining with PInf 7.5991847e+05 5851s
69301 PPushes remaining with PInf 7.5593167e+05 5857s
67805 PPushes remaining with PInf 7.5469499e+05 5863s
67047 PPushes remaining with PInf 7.5369921e+05 5865s
65556 PPushes remaining with PInf 7.4886577e+05 5872s
63981 PPushes remaining with PInf 7.4840725e+05 5878s
63249 PPushes remaining with PInf 7.4783483e+05 5881s
61836 PPushes remaining with PInf 7.4705676e+05 5888s
61109 PPushes remaining with PInf 7.4661242e+05 5891s
59639 PPushes remaining with PInf 7.4567360e+05 5897s
58927 PPushes remaining with PInf 7.4523860e+05 5901s
58191 PPushes remaining with PInf 1.2986194e+07 5905s
56511 PPushes remaining with PInf 1.2680117e+07 5913s
55729 PPushes remaining with PInf 1.2674518e+07 5917s
54886 PPushes remaining with PInf 1.2668730e+07 5921s
53414 PPushes remaining with PInf 1.2655689e+07 5929s
52617 PPushes remaining with PInf 1.2645898e+07 5932s
51861 PPushes remaining with PInf 1.2634822e+07 5936s
50358 PPushes remaining with PInf 1.2609041e+07 5944s
49527 PPushes remaining with PInf 1.2581144e+07 5948s
48703 PPushes remaining with PInf 1.2571876e+07 5952s
47959 PPushes remaining with PInf 1.2561405e+07 5955s
46434 PPushes remaining with PInf 1.2541918e+07 5964s
45557 PPushes remaining with PInf 1.2517410e+07 5969s
44844 PPushes remaining with PInf 1.2509623e+07 5972s
44115 PPushes remaining with PInf 1.2497385e+07 5976s
43408 PPushes remaining with PInf 1.2488707e+07 5981s
42561 PPushes remaining with PInf 1.2468543e+07 5985s
41000 PPushes remaining with PInf 1.2450792e+07 5994s
40276 PPushes remaining with PInf 1.2430913e+07 5998s
39514 PPushes remaining with PInf 1.2414627e+07 6003s
38782 PPushes remaining with PInf 1.2395365e+07 6007s
38002 PPushes remaining with PInf 1.2372239e+07 6012s
37253 PPushes remaining with PInf 1.2350212e+07 6016s
36493 PPushes remaining with PInf 1.2325819e+07 6020s
34965 PPushes remaining with PInf 1.2292398e+07 6029s
34221 PPushes remaining with PInf 1.2279059e+07 6032s
33392 PPushes remaining with PInf 1.2270358e+07 6037s
32643 PPushes remaining with PInf 1.2266845e+07 6042s
31860 PPushes remaining with PInf 1.2253712e+07 6047s
31131 PPushes remaining with PInf 1.2234220e+07 6051s
30380 PPushes remaining with PInf 1.2219376e+07 6056s
29619 PPushes remaining with PInf 1.2213385e+07 6061s
28911 PPushes remaining with PInf 1.2202000e+07 6066s
28204 PPushes remaining with PInf 1.2186953e+07 6071s
27439 PPushes remaining with PInf 1.2178918e+07 6076s
26726 PPushes remaining with PInf 1.2151557e+07 6081s
25971 PPushes remaining with PInf 1.2138382e+07 6087s
25239 PPushes remaining with PInf 1.2123871e+07 6092s
24506 PPushes remaining with PInf 1.2110483e+07 6097s
24040 PPushes remaining with PInf 3.2556343e+07 6101s
23259 PPushes remaining with PInf 3.2312327e+07 6107s
22455 PPushes remaining with PInf 3.2162325e+07 6112s
21644 PPushes remaining with PInf 3.2140975e+07 6118s
20816 PPushes remaining with PInf 3.2111715e+07 6124s
20074 PPushes remaining with PInf 3.2061782e+07 6129s
19254 PPushes remaining with PInf 3.2031393e+07 6135s
18478 PPushes remaining with PInf 3.1999841e+07 6141s
17728 PPushes remaining with PInf 3.1977055e+07 6147s
16894 PPushes remaining with PInf 3.1968092e+07 6153s
16142 PPushes remaining with PInf 3.1949058e+07 6158s
15375 PPushes remaining with PInf 3.1923496e+07 6164s
14591 PPushes remaining with PInf 3.1899421e+07 6170s
13841 PPushes remaining with PInf 3.1880419e+07 6176s
13087 PPushes remaining with PInf 3.1865697e+07 6182s
12313 PPushes remaining with PInf 3.1851053e+07 6188s
11572 PPushes remaining with PInf 3.1830601e+07 6194s
10801 PPushes remaining with PInf 3.1819978e+07 6200s
10055 PPushes remaining with PInf 3.1805400e+07 6206s
9327 PPushes remaining with PInf 3.1789487e+07 6213s
8593 PPushes remaining with PInf 3.1782185e+07 6218s
7851 PPushes remaining with PInf 3.1770887e+07 6225s
7127 PPushes remaining with PInf 3.1760942e+07 6231s
6412 PPushes remaining with PInf 3.1752759e+07 6237s
5697 PPushes remaining with PInf 3.1741806e+07 6243s
4985 PPushes remaining with PInf 3.1727682e+07 6250s
4270 PPushes remaining with PInf 3.1711892e+07 6257s
3545 PPushes remaining with PInf 3.1698374e+07 6263s
2836 PPushes remaining with PInf 3.1685509e+07 6270s
2089 PPushes remaining with PInf 3.1659600e+07 6277s
1368 PPushes remaining with PInf 3.1588630e+07 6285s
637 PPushes remaining with PInf 3.1568703e+07 6292s
0 PPushes remaining with PInf 3.1541981e+07 6298sPush phase complete: Pinf 3.1541981e+07, Dinf 5.0000000e+01 6298s
Root simplex log...Iteration Objective Primal Inf. Dual Inf. Time
355566 3.4160000e+03 0.000000e+00 5.000000e+01 6300s
355723 3.4160000e+03 7.409556e+05 0.000000e+00 6325s
356395 3.4160002e+03 1.441547e+06 0.000000e+00 6374s
357067 3.4160006e+03 1.918380e+06 0.000000e+00 6423s
357739 3.4160008e+03 1.756475e+06 0.000000e+00 6471s
358411 3.4160013e+03 1.020875e+06 0.000000e+00 6523s
359083 3.4160024e+03 1.729014e+06 0.000000e+00 6577s
359755 3.4160032e+03 6.432424e+05 0.000000e+00 6629s
360427 3.4160045e+03 2.414983e+06 0.000000e+00 6684s
361099 3.4160059e+03 1.493935e+06 0.000000e+00 6740s
361771 3.4160069e+03 7.436340e+05 0.000000e+00 6794s
362443 3.4160086e+03 1.392075e+06 0.000000e+00 6850s
363115 3.4160102e+03 1.240510e+06 0.000000e+00 6906s
363787 3.4160118e+03 5.373453e+05 0.000000e+00 6965s
364459 3.4160128e+03 5.797593e+05 0.000000e+00 7023s
365131 3.4160143e+03 1.651136e+06 0.000000e+00 7083s
365803 3.4160162e+03 9.908922e+05 0.000000e+00 7144s
366475 3.4160182e+03 1.678758e+06 0.000000e+00 7205s
367147 3.4160200e+03 1.673700e+06 0.000000e+00 7269s
367819 3.4160208e+03 1.405406e+06 0.000000e+00 7332s
368491 3.4160215e+03 1.581545e+06 0.000000e+00 7393s
369163 3.4160229e+03 5.584824e+06 0.000000e+00 7458s
369835 3.4160242e+03 2.217298e+06 0.000000e+00 7522s
370507 3.4160254e+03 2.946248e+06 0.000000e+00 7589s
371179 3.4160267e+03 2.477525e+06 0.000000e+00 7658s
371851 3.4160281e+03 4.211708e+06 0.000000e+00 7724s
372523 3.4160314e+03 6.520942e+06 0.000000e+00 7790s
373195 3.4160340e+03 3.068084e+06 0.000000e+00 7857s
373867 3.4160363e+03 2.670572e+06 0.000000e+00 7925s
374539 3.4160385e+03 1.912603e+06 0.000000e+00 7993s
375211 3.4160410e+03 3.984164e+06 0.000000e+00 8061s
375883 3.4160473e+03 5.521958e+06 0.000000e+00 8125s
376555 3.4160517e+03 4.072520e+06 0.000000e+00 8195s
377227 3.4160560e+03 2.451779e+07 0.000000e+00 8265s
377899 3.4160603e+03 4.916026e+06 0.000000e+00 8336s
378571 3.4160642e+03 4.623868e+06 0.000000e+00 8404s
379243 3.4160810e+03 1.020996e+07 0.000000e+00 8454s
379915 3.4160882e+03 8.376712e+06 0.000000e+00 8513s
380587 3.4160948e+03 1.537799e+07 0.000000e+00 8582s
381259 3.4160999e+03 1.615006e+07 0.000000e+00 8648s
381931 3.4161056e+03 8.374207e+06 0.000000e+00 8713s
382603 3.4161121e+03 3.696683e+06 0.000000e+00 8784s
383275 3.4161163e+03 4.342371e+06 0.000000e+00 8843s
383947 3.4161216e+03 6.158361e+08 0.000000e+00 8920s
384619 3.4161264e+03 4.995364e+06 0.000000e+00 8986s
385291 3.4161322e+03 7.655202e+06 0.000000e+00 9057s
385963 3.4161666e+03 1.038858e+07 0.000000e+00 9121s
386635 3.4161851e+03 1.286930e+07 0.000000e+00 9189s
387307 3.4162026e+03 2.461398e+07 0.000000e+00 9256s
387979 3.4162179e+03 1.834058e+07 0.000000e+00 9323s
388651 3.4162345e+03 1.609154e+08 0.000000e+00 9389s
389323 3.4162497e+03 1.565149e+07 0.000000e+00 9458s
389995 3.4162648e+03 4.975006e+06 0.000000e+00 9533s
390667 3.4162776e+03 6.304048e+07 0.000000e+00 9607s
391339 3.4162888e+03 2.301130e+07 0.000000e+00 9680s
392011 3.4162990e+03 9.743646e+06 0.000000e+00 9754s
392683 3.4163101e+03 2.338373e+07 0.000000e+00 9830s
393355 3.4163211e+03 4.911352e+07 0.000000e+00 9896s
394027 3.4163309e+03 1.558408e+07 0.000000e+00 9974s
394699 3.4163399e+03 1.220973e+07 0.000000e+00 10049s
395371 3.4163503e+03 3.646481e+07 0.000000e+00 10124s
396043 3.4163602e+03 1.540412e+07 0.000000e+00 10202s
396573 3.4163677e+03 1.948240e+07 0.000000e+00 10265s
397013 3.4163732e+03 8.143033e+07 0.000000e+00 10324s
397685 3.4163810e+03 3.546714e+06 0.000000e+00 10397s
398357 3.4163904e+03 3.310388e+07 0.000000e+00 10471s
399029 3.4163988e+03 6.909620e+06 0.000000e+00 10540s
399701 3.4164069e+03 4.863336e+06 0.000000e+00 10618s
400373 3.4164164e+03 1.638794e+07 0.000000e+00 10699s
401045 3.4164277e+03 6.807897e+06 0.000000e+00 10773s
401695 3.4164350e+03 4.596395e+07 0.000000e+00 10852s
402225 3.4164419e+03 1.405982e+07 0.000000e+00 10911s
402695 3.4164477e+03 5.105177e+06 0.000000e+00 10966s
403075 3.4164517e+03 1.417707e+07 0.000000e+00 11013s
403475 3.4164563e+03 1.220566e+07 0.000000e+00 11060s
403875 3.4164605e+03 1.127120e+07 0.000000e+00 11108s
404245 3.4164647e+03 1.494047e+07 0.000000e+00 11160s
404917 3.4164721e+03 6.828626e+06 0.000000e+00 11228s
405589 3.4164806e+03 4.503878e+06 0.000000e+00 11306s
406261 3.4164880e+03 5.171731e+07 0.000000e+00 11391s
406933 3.4164966e+03 9.874363e+06 0.000000e+00 11459s
407605 3.4165032e+03 8.518848e+06 0.000000e+00 11543s
408277 3.4165107e+03 8.246188e+07 0.000000e+00 11612s
408949 3.4165177e+03 5.383380e+06 0.000000e+00 11698s
409621 3.4165254e+03 1.412614e+07 0.000000e+00 11768s
410293 3.4165330e+03 4.636516e+07 0.000000e+00 11854s
410965 3.4165398e+03 7.421082e+06 0.000000e+00 11923s
411637 3.4165457e+03 4.976317e+06 0.000000e+00 12003s
412309 3.4165523e+03 6.487004e+06 0.000000e+00 12087s
412981 3.4165587e+03 7.581628e+06 0.000000e+00 12170s
413601 3.4165655e+03 5.811984e+06 0.000000e+00 12247s
414141 3.4166098e+03 3.626580e+06 0.000000e+00 12313s
414711 3.4166561e+03 8.325089e+06 0.000000e+00 12372s
415221 3.4166783e+03 2.274173e+08 0.000000e+00 12431s
415771 3.4166992e+03 3.710908e+06 0.000000e+00 12489s
416231 3.4167156e+03 4.637718e+06 0.000000e+00 12546s
416771 3.4167305e+03 2.711201e+06 0.000000e+00 12606s
417271 3.4167447e+03 1.515338e+07 0.000000e+00 12668s
417781 3.4167606e+03 6.187077e+06 0.000000e+00 12728s
418301 3.4167725e+03 5.571272e+06 0.000000e+00 12787s
418761 3.4167810e+03 1.306086e+06 0.000000e+00 12844s
419231 3.4167885e+03 1.875391e+06 0.000000e+00 12903s
419731 3.4167992e+03 2.909786e+06 0.000000e+00 12964s
420291 3.4168114e+03 1.152826e+06 0.000000e+00 13036s
420963 3.4168255e+03 3.118045e+06 0.000000e+00 13102s
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561383 3.4178227e+03 2.768386e+07 0.000000e+00 31075s
561863 3.4178247e+03 5.829412e+06 0.000000e+00 31135s
562333 3.4178268e+03 1.588502e+06 0.000000e+00 31193s
562813 3.4178290e+03 4.081890e+06 0.000000e+00 31253s
563253 3.4178306e+03 1.097932e+06 0.000000e+00 31313s
563753 3.4178323e+03 7.443779e+07 0.000000e+00 31380s
564233 3.4178338e+03 8.150212e+05 0.000000e+00 31441s
564743 3.4178359e+03 1.917229e+06 0.000000e+00 31508s
565243 3.4178381e+03 4.867394e+06 0.000000e+00 31571s
565683 3.4178398e+03 1.623547e+07 0.000000e+00 31629s
566123 3.4178416e+03 2.165440e+07 0.000000e+00 31689s
566563 3.4178433e+03 6.083301e+06 0.000000e+00 31746s
567063 3.4178455e+03 1.568461e+06 0.000000e+00 31811s
567593 3.4178477e+03 2.858809e+06 0.000000e+00 31881s
568093 3.4178499e+03 1.452895e+06 0.000000e+00 31949s
568563 3.4178519e+03 9.259340e+05 0.000000e+00 32014s
569073 3.4178539e+03 9.692128e+05 0.000000e+00 32079s
569543 3.4178555e+03 2.952762e+07 0.000000e+00 32138s
570013 3.4178573e+03 8.646226e+05 0.000000e+00 32197s
570463 3.4178591e+03 1.818978e+06 0.000000e+00 32254s
570973 3.4178609e+03 1.880807e+06 0.000000e+00 32318s
571463 3.4178626e+03 7.283963e+06 0.000000e+00 32382s
572093 3.4178650e+03 3.680364e+06 0.000000e+00 32459s
572633 3.4178671e+03 1.587726e+06 0.000000e+00 32529s
573133 3.4178690e+03 1.905526e+06 0.000000e+00 32591s0 -
Hi, any update on this ?
thank you very much for your kind help
0 -
If you have a feasible solution for objective zero, you could provide this as a MIP start. There are different ways to do this. You can set the Start attributes to the corresponding warm-start values or read a .mst or .sol solution file with Model.read(). You could also let Gurobi solve the model without setting an objective, then change the model by setting the objective and optimize again. Gurobi should then automatically use the previous solution as a MIP start.
However, from your log, it seems that the solver is already struggling when solving the root relaxation (in particular, in the simplex phase). A MIP start will not help with that. You could try setting DegenMoves=0 or tightening BarConvTol.
0
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