Any Feasible settings in yalmip to deal with excessively long “solvertime”？

[lzmssyld]

Dear sir！
1.Problem description
I modeled a scheduling problem where the decision variable space gradually expands.As the dimensions of decision variables increase, I faced the following problems：excessively long “solvertime”.
Here is my pseudocode：
ops = sdpsettings('solver' , 'gurobi' );
ops = sdpsettings(ops,'usex0',1);
sol= optimize(F,objective,ops);%

The following is the text in the command line window:

Gurobi Optimizer version 11.0.2 build v11.0.2rc0 (win64 - Windows 10.0 (19045.2))

CPU model: Intel(R) Core(TM) i5-8300H CPU @ 2.30GHz, instruction set [SSE2|AVX|AVX2]
Thread count: 4 physical cores, 8 logical processors, using up to 8 threads
Optimize a model with 23565 rows, 6000 columns and 56700 nonzeros
Model fingerprint: 0x5dd691eb
Variable types: 1800 continuous, 4200 integer (3600 binary)
Coefficient statistics:
  Matrix range     [1e+00, 2e+04]
  Objective range  [1e+00, 1e+00]
  Bounds range     [1e+00, 1e+00]
 RHS range        [1e+00, 2e+04]
Presolve removed 4546 rows and 2585 columns
Presolve time: 4.38s
Presolved: 19019 rows, 3415 columns, 50066 nonzeros
Variable types: 0 continuous, 3415 integer (1451 binary)
Root relaxation presolved: 19019 rows, 3415 columns, 50066 nonzeros


Root relaxation: objective 9.750500e+04, 747 iterations, 0.05 seconds (0.05 work units)

    Nodes    |    Current Node    |     Objective Bounds      |     Work
Expl Unexpl |  Obj  Depth IntInf | Incumbent    BestBd   Gap | It/Node Time

     0     0 97505.0000    0   29          - 97505.0000      -     -    4s
H    0     0                    99771.000000 97505.0000  2.27%     -    5s
H    0     0                    99702.000000 97505.0000  2.20%     -    5s
     0     0 97505.0000    0  321 99702.0000 97505.0000  2.20%     -    5s
........
 1598223 732601 98542.7793   45   19 98847.0000 98225.0000  0.63%  11.5 1486s
 1603052 734535 98225.0494   39   20 98847.0000 98225.0000  0.63%  11.5 1491s
 1606616 735916 98695.0000   41    6 98847.0000 98225.0000  0.63%  11.5 1495s
 1611516 737801 98405.0000   40   33 98847.0000 98225.0000  0.63%  11.5 1501s
.......

2.Some attempts
I am very certain that there is a feasible solution for this problem.Can I try some other settings besides using the command 'ops = sdpsettings(ops,'timelimit',180);'？If i used the command 'ops = sdpsettings(ops,'timelimit',180)‘，the quality of the solution became very poor.

Is the 'Gap' setting too small? Or do I need to set "MIPfocus=2"?

[johanlofberg]

https://yalmip.github.io/slowmilp

[lzmssyld]

Thank for Mr. Lofberg's guidance. In the end, I solved the problem by revising the model to reduce the number of constraints.