Section 4.5.4: Design of a cantilever beam: recursive formulation (GP)

% Boyd & Vandenberghe "Convex Optimization"
% (a figure is generated)
% Almir Mutapcic 02/08/06
%
% We have a segmented cantilever beam with N segments. Each segment
% has a unit length and variable width and height (rectangular profile).
% The goal is minimize the total volume of the beam, over all segment
% widths w_i and heights h_i, subject to constraints on aspect ratios,
% maximum allowable stress in the material, vertical deflection y, etc.
%
% The problem can be posed as a geometric program (posynomial form)
%     minimize   sum( w_i* h_i)
%         s.t.   w_min <= w_i <= w_max,       for all i = 1,...,N
%                h_min <= h_i <= h_max
%                S_min <= h_i/w_i <= S_max
%                6*i*F/(w_i*h_i^2) <= sigma_max
%                y_1 <= y_max
%
% with variables w_i and h_i (i = 1,...,N).
% For other definitions consult the book.
% (See exercise 4.31 for a non-recursive formulation.)

% optimization variables
N = 8;

% constants
wmin = .1; wmax = 100;
hmin = .1; hmax = 6;
Smin = 1/5; Smax = 5;
sigma_max = 1;
ymax = 10;
E = 1; F = 1;

cvx_begin gp
  % optimization variables
  variables w(N) h(N)

  % setting up variables relations
  % (recursive formulation)
  v = cvx( zeros(N+1,1) );
  y = cvx( zeros(N+1,1) );
  for i = N:-1:1
    fprintf(1,'Building recursive relations for index: %d\n',i);
    v(i) = 12*(i-1/2)*F/(E*w(i)*h(i)^3) + v(i+1);
    y(i) = 6*(i-1/3)*F/(E*w(i)*h(i)^3)  + v(i+1) + y(i+1);
  end

  % objective is the total volume of the beam
  % obj = sum of (widths*heights*lengths) over each section
  % (recall that the length of each segment is set to be 1)
  minimize( w'*h )
  subject to
    % constraint set
    wmin <= w; w <= wmax;
    hmin <= h; h <= hmax;
    Smin <= h./w; h./w <= Smax;
    6*F*[1:N]'./(w.*(h.^2)) <= sigma_max;
    y(1) <= ymax;
cvx_end

% display results
disp('The optimal widths and heights are: ');
w, h
fprintf(1,'The optimal minimum volume of the beam is %3.4f.\n', sum(w.*h))

% plot the 3D model of the optimal cantilever beam
figure, clf
cantilever_beam_plot([h; w])
Building recursive relations for index: 8
Building recursive relations for index: 7
Building recursive relations for index: 6
Building recursive relations for index: 5
Building recursive relations for index: 4
Building recursive relations for index: 3
Building recursive relations for index: 2
Building recursive relations for index: 1
 
Successive approximation method to be employed.
   SDPT3 will be called several times to refine the solution.
   Original size: 125 variables, 38 equality constraints
   For improved efficiency, SDPT3 is solving the dual problem.
   Approximation size: 310 variables, 153 equality constraints
-----------------------------------------------------------------
 Target     Conic    Solver
Precision   Error    Status
---------------------------
1.221e-04  2.205e+00  Solved
1.221e-04  6.141e-02  Solved
1.221e-04  0.000e+00  Solved
1.490e-08  1.102e-06  Solved
1.490e-08  0.000e+00  Solved
-----------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +42.3965
The optimal widths and heights are: 

w =

    0.6214
    0.7830
    0.9060
    1.0124
    1.1004
    1.1762
    1.2000
    1.3333


h =

    3.1072
    3.9149
    4.5298
    5.0620
    5.5019
    5.8811
    6.0000
    6.0000

The optimal minimum volume of the beam is 42.3965.