no solution found !!

Mohamed Soliman

unread,

Sep 22, 2021, 1:55:02 PM9/22/21

to YALMIP

Hello Johan,

In the attached code I want to implement a car (with linear dynamics) equipped with lidar senor. The optimizer should predict only one step ahead within the field of view (which I assume it as a box) . The optimizer can predict in the current field of view or in the previous lidar reading. According to the objective function which is minimizing a goal point, a point from the current lidar measurement should be selected.

When I code the mathematical formulation, the optimizer does not give me any sol

BR

M.Soliman

planner2.m

Johan Löfberg

unread,

Sep 22, 2021, 2:21:37 PM9/22/21

to YALMIP

https://yalmip.github.io/debugginginfeasible

and then as always, you don't use optimizer until you actually know code works with optimize, and you never turn off display (as you have now) until things work

Mohamed Soliman

unread,

Sep 22, 2021, 2:39:18 PM9/22/21

to YALMIP

I follow the link you sent and use optimize(constraints,[],sdpsettings('solver','gurobi'))

yalmipversion: '20200930'

matlabversion: '9.9.0.1467703 (R2020b)'

yalmiptime: 0.21704

solvertime: 0.10496

info: 'Successfully solved (GUROBI-GUROBI)'

problem: 0

how I turn on display?

Thanks

Mohamed Soliman

unread,

Sep 22, 2021, 2:41:07 PM9/22/21

to YALMIP

Also when I use optimize(constraints,objective,sdpsettings('solver','gurobi')) it gives me

yalmipversion: '20200930'

matlabversion: '9.9.0.1467703 (R2020b)'

yalmiptime: 0.45011

solvertime: 0.23052

info: 'Successfully solved (GUROBI-GUROBI)'

problem: 0

>>

On Wednesday, September 22, 2021 at 8:21:37 PM UTC+2 Johan Löfberg wrote:

Mohamed Soliman

unread,

Sep 22, 2021, 2:46:49 PM9/22/21

to YALMIP

optimize(constraints,objective,sdpsettings('solver','gurobi','verbose',1))

Gurobi Optimizer version 9.1.2 build v9.1.2rc0 (linux64)

Thread count: 4 physical cores, 8 logical processors, using up to 8 threads

Optimize a model with 17 rows, 16 columns and 28 nonzeros

Model fingerprint: 0xb72e5dd0

Model has 14 quadratic objective terms

Variable types: 14 continuous, 2 integer (2 binary)

Coefficient statistics:

Matrix range [5e-03, 1e+00]

Objective range [0e+00, 0e+00]

QObjective range [2e+00, 4e+00]

Bounds range [1e+00, 1e+00]

RHS range [1e+00, 1e+02]

Presolve removed 16 rows and 11 columns

Presolve time: 0.00s

Presolved: 1 rows, 5 columns, 4 nonzeros

Presolved model has 6 quadratic objective terms

Variable types: 5 continuous, 0 integer (0 binary)

Presolve time: 0.09s

Presolved: 1 rows, 5 columns, 4 nonzeros

Presolved model has 6 quadratic objective terms

Root barrier log...

Ordering time: 0.00s

Barrier statistics:

Free vars : 5

AA' NZ : 3.000e+00

Factor NZ : 6.000e+00

Factor Ops : 1.400e+01 (less than 1 second per iteration)

Threads : 1

Objective Residual

Iter Primal Dual Primal Dual Compl Time

0 7.68935161e-10 -6.26562500e+03 1.00e+03 5.87e-07 1.00e+06 0s

1 1.07864430e-05 -6.22677209e+03 9.99e-01 7.47e-05 2.55e+03 0s

2 1.24907040e-03 -3.92732195e+02 9.99e-07 5.28e-08 9.82e+01 0s

3 1.24786283e-03 -4.54656566e-01 1.61e-10 2.91e-11 1.14e-01 0s

4 6.62152250e-04 -1.15421266e-03 4.01e-12 1.37e-08 4.54e-04 0s

5 9.50951799e-05 -1.53060889e-04 3.77e-12 1.20e-08 6.23e-05 0s

6 1.37609883e-05 -1.58619848e-05 3.62e-12 2.47e-09 7.42e-06 0s

7 1.95758040e-06 -2.28425785e-06 3.95e-11 8.62e-10 1.06e-06 0s

8 2.78661554e-07 -3.17947441e-07 6.68e-11 3.14e-10 1.49e-07 0s

9 4.02136123e-08 -4.43417732e-08 2.63e-10 1.17e-10 2.12e-08 0s

10 6.36654596e-09 -5.62340864e-09 1.10e-10 4.39e-11 3.00e-09 0s

11 1.56272418e-09 -1.37868858e-10 1.04e-09 9.71e-12 4.26e-10 0s

Barrier solved model in 11 iterations and 0.14 seconds

Optimal objective 1.56272418e-09

Root relaxation: objective 1.562724e-09, 0 iterations, 0.06 seconds

Nodes | Current Node | Objective Bounds | Work

Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time

* 0 0 0 0.0000000 0.00000 0.00% - 0s

Explored 0 nodes (0 simplex iterations) in 0.16 seconds

Thread count was 8 (of 8 available processors)

Solution count 1: 1.56342e-09

Optimal solution found (tolerance 1.00e-04)

Best objective 1.566149876453e-09, best bound 1.562724178396e-09, gap 0.0000%

ans =

struct with fields:

yalmipversion: '20200930'

matlabversion: '9.9.0.1467703 (R2020b)'

yalmiptime: 0.20439

solvertime: 0.2011

info: 'Successfully solved (GUROBI-GUROBI)'

problem: 0

Johan Löfberg

unread,

Sep 22, 2021, 2:58:11 PM9/22/21

to YALMIP

So no problems then (assuming you have added constraints on initial conditons etc to actually solve the problem you want)

verbosity is controlled with the verbose option. to ensure it displays when using optimizer, you will have to increase it to 2, as it by default drops the verbosity level by 1 level

Johan Löfberg

unread,

Sep 22, 2021, 3:08:09 PM9/22/21

to YALMIP

and why are you using the horzcat function instead of just concatenating as usual

onsdag 22 september 2021 kl. 20:39:18 UTC+2 skrev mosoli...@gmail.com:

Reply all

Reply to author

Forward