% 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    <= wmax;
    hmin <= h    <= hmax;
    Smin <= 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.
   For improved efficiency, SeDuMi is solving the dual problem.
   SeDuMi will be called several times to refine the solution.
   Original size: 126 variables, 39 equality constraints
   23 exponentials add 184 variables, 115 equality constraints
-----------------------------------------------------------------
 Cones  |             Errors              |
Mov/Act | Centering  Exp cone   Poly cone | Status
--------+---------------------------------+---------
 23/ 23 | 6.487e+00  2.207e+00  0.000e+00 | Solved
 23/ 23 | 1.520e+00  1.942e-01  2.724e-07 | Solved
 23/ 23 | 1.644e-01  2.074e-03  5.029e-08 | Solved
 22/ 23 | 8.370e-03  5.600e-06  4.432e-08 | Solved
  9/ 23 | 5.035e-04  5.092e-08  4.441e-08 | Solved
  0/ 23 | 1.039e-04  4.409e-08  4.400e-08 | 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
    4.5299
    5.0621
    5.5019
    5.8810
    6.0000
    6.0000

The optimal minimum volume of the beam is 42.3965.