I have an optimization problem that is multidimensional and rather complex. My nonlinear constraints aren’t continuous and the objective function is continuous and differentiable. However, I’m first trying to just find a feasible solution and I’m using patternsearch to do this:
opts = optimoptions(‘patternsearch’,’Algorithm’,’classic’ , ‘Display’, ‘iter’, ‘UseParallel’, true, ‘UseCompletePoll’,true,’PollMethod’,’MADSPositiveBasis2N’);
x0 = patternsearch(@(x)J_constraints(x, lowerLimit, upperLimit, z_des, angleBounds) , x0, [],[],[],[],lb,ub,[],opts);
The thing is that my J_constraints function (representing the nonlinear constraints from earlier) needs to be negative and has significant regions in which it is constant. Therefore often when I run patternsearch it stays at the same point since all of the mesh points have actually the same value as the current point:
Iter Func-count f(x) MeshSize Method
95 4034 2270 6.985e-10 Refine Mesh
96 4034 2270 3.492e-10 Refine Mesh
97 4034 2270 1.746e-10 Refine Mesh
98 4034 2270 8.731e-11 Refine Mesh
99 4034 2270 4.366e-11 Refine Mesh
100 4034 2270 2.183e-11 Refine Mesh
101 4034 2270 1.091e-11 Refine Mesh
102 4034 2270 5.457e-12 Refine Mesh
103 4034 2270 2.728e-12 Refine Mesh
104 4034 2270 1.364e-12 Refine Mesh
105 4034 2270 6.821e-13 Refine Mesh
What I would like it to do is to change the point even if the objective function is the same in the best point from the mesh and of course effectively increase the mesh size (consider the poll successful even though the objective function stays the same). Is there a way to do this? I don’t care that much about other parameters (whether I use the "classic" version or the "nups" one, whether it’s MADS, GPS or GSS etc.)
Essentially, I would like to change the PollMethod. Is there any way to do this?
I’ve also tried using the SearchFcn option, but wasn’t quite successful because I the mesh points are not available within the function.
Thank you in advance for any help!I have an optimization problem that is multidimensional and rather complex. My nonlinear constraints aren’t continuous and the objective function is continuous and differentiable. However, I’m first trying to just find a feasible solution and I’m using patternsearch to do this:
opts = optimoptions(‘patternsearch’,’Algorithm’,’classic’ , ‘Display’, ‘iter’, ‘UseParallel’, true, ‘UseCompletePoll’,true,’PollMethod’,’MADSPositiveBasis2N’);
x0 = patternsearch(@(x)J_constraints(x, lowerLimit, upperLimit, z_des, angleBounds) , x0, [],[],[],[],lb,ub,[],opts);
The thing is that my J_constraints function (representing the nonlinear constraints from earlier) needs to be negative and has significant regions in which it is constant. Therefore often when I run patternsearch it stays at the same point since all of the mesh points have actually the same value as the current point:
Iter Func-count f(x) MeshSize Method
95 4034 2270 6.985e-10 Refine Mesh
96 4034 2270 3.492e-10 Refine Mesh
97 4034 2270 1.746e-10 Refine Mesh
98 4034 2270 8.731e-11 Refine Mesh
99 4034 2270 4.366e-11 Refine Mesh
100 4034 2270 2.183e-11 Refine Mesh
101 4034 2270 1.091e-11 Refine Mesh
102 4034 2270 5.457e-12 Refine Mesh
103 4034 2270 2.728e-12 Refine Mesh
104 4034 2270 1.364e-12 Refine Mesh
105 4034 2270 6.821e-13 Refine Mesh
What I would like it to do is to change the point even if the objective function is the same in the best point from the mesh and of course effectively increase the mesh size (consider the poll successful even though the objective function stays the same). Is there a way to do this? I don’t care that much about other parameters (whether I use the "classic" version or the "nups" one, whether it’s MADS, GPS or GSS etc.)
Essentially, I would like to change the PollMethod. Is there any way to do this?
I’ve also tried using the SearchFcn option, but wasn’t quite successful because I the mesh points are not available within the function.
Thank you in advance for any help! I have an optimization problem that is multidimensional and rather complex. My nonlinear constraints aren’t continuous and the objective function is continuous and differentiable. However, I’m first trying to just find a feasible solution and I’m using patternsearch to do this:
opts = optimoptions(‘patternsearch’,’Algorithm’,’classic’ , ‘Display’, ‘iter’, ‘UseParallel’, true, ‘UseCompletePoll’,true,’PollMethod’,’MADSPositiveBasis2N’);
x0 = patternsearch(@(x)J_constraints(x, lowerLimit, upperLimit, z_des, angleBounds) , x0, [],[],[],[],lb,ub,[],opts);
The thing is that my J_constraints function (representing the nonlinear constraints from earlier) needs to be negative and has significant regions in which it is constant. Therefore often when I run patternsearch it stays at the same point since all of the mesh points have actually the same value as the current point:
Iter Func-count f(x) MeshSize Method
95 4034 2270 6.985e-10 Refine Mesh
96 4034 2270 3.492e-10 Refine Mesh
97 4034 2270 1.746e-10 Refine Mesh
98 4034 2270 8.731e-11 Refine Mesh
99 4034 2270 4.366e-11 Refine Mesh
100 4034 2270 2.183e-11 Refine Mesh
101 4034 2270 1.091e-11 Refine Mesh
102 4034 2270 5.457e-12 Refine Mesh
103 4034 2270 2.728e-12 Refine Mesh
104 4034 2270 1.364e-12 Refine Mesh
105 4034 2270 6.821e-13 Refine Mesh
What I would like it to do is to change the point even if the objective function is the same in the best point from the mesh and of course effectively increase the mesh size (consider the poll successful even though the objective function stays the same). Is there a way to do this? I don’t care that much about other parameters (whether I use the "classic" version or the "nups" one, whether it’s MADS, GPS or GSS etc.)
Essentially, I would like to change the PollMethod. Is there any way to do this?
I’ve also tried using the SearchFcn option, but wasn’t quite successful because I the mesh points are not available within the function.
Thank you in advance for any help! optimization, pattern search, poll method, feasibility search MATLAB Answers — New Questions

​